Search results for: medical diagnostic imaging

Authors: Lelika Lazarus, Reshma Sookrajh, Kapil S. Satyapal

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Reflecting on teaching is commonly cited as a fundamental practice for personal and professional development. Educational research into the scholarship of teaching and learning anatomy includes engaging in discipline specific literature on teaching, reflecting on individual teaching methods and communicating these findings to peers. The aim of this paper is to formally assess the opinions of senior anatomy instructors regarding the state of anatomical knowledge at their respective institutions. The context of the paper derives from ongoing debates about the perceived decline in standards of anatomical knowledge of medical students and postgraduate learners. An open ended questionnaire was devised consisting of eight direct questions seeking opinions on anatomy teaching, knowledge, and potential educational developments and general thoughts on the teaching of anatomy to medical students. These were distributed to senior anatomy Faculty (identified by the author by their affiliation with the Anatomical Society of Southern Africa) based at the eight national medical schools within the country. A number of key themes emerged. Most senior faculty felt that the standard of medical education at their respective institutions was ‘good.’. However, emphasis was also placed on the ‘quality of teaching’ incorporating clinical scenarios. There were also indications that staff are split into those that are keen to do research and those that are happy to provide teaching to medical students as their primary function. Several challenges were also highlighted such as time constraints within the medical curriculum, the lack of cadavers to reinforce knowledge and gain depth perception and lack of appropriately qualified staff. Recommendations included fostering partnerships with both clinicians and medical scientists into the anatomy curriculum thus improving teaching and research.

Keywords: anatomy, education, reflection, teaching

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Authors: H. Al-Khalaifa, A. Al-Nasser

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The viewpoint towards the use of drugs or vaccines against avian parasitic diseases is one of the most striking challenges in avian medical parasitology. This includes many difficulties associated with drug resistance and in developing prophylactic vaccines. In many instances, the potential success of a vaccination in controlling parasitic diseases in poultry is well-documented. However, some medical, technical and financial limitations are still paramount. On the other hand, chemotherapy is not very well-recommended due to a number of medical limitations. But in the absence of an effective vaccine, drugs are used against parasitic diseases. This paper sheds light on some the advantages and disadvantages of using vaccination and drugs in controlling parasitic diseases in poultry species. The usage of chemotherapeutic drugs is discussed with some examples. Then, more light will be shed on using vaccines as a potentially effective and promising control tool.

Keywords: drugs, parasitology, poultry, vaccines

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Authors: Hannah Yael Ephraim

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During reproductive age (between 15 and 44), women are particularly susceptible to psychiatric illness. Depression and anxiety disorders are especially common for women during reproductive age. Women of reproductive age are also at greater risk for multiple physical conditions during this time. Existing literature focuses on the impact of mental health on physical health, showing that people with anxiety and depression repeatedly show greater physical health risk among those with developing chronic medical illness. However, there is limited research on the impact physical health has on mental health in women of reproductive age, a large and vulnerable population. For this reason, the current study seeks to ask the following questions: are women of reproductive age with a diagnosis of a chronic physical condition more likely to experience symptoms of mental illness than women without a diagnosis of a chronic physical condition? Does the type of physical illness relate to signs and symptoms of depression and anxiety? A quasi-experimental research design was implemented to compare the mental health outcomes of women with the diagnosis of chronic medical conditions and women without the diagnosis of a chronic medical condition. Quantitative data was collected through an anonymous ten-minute Qualtrics survey. The survey was sent out through multiple online platforms. The sample includes two groups of women: one group with the diagnosis of a chronic medical illness, and one group without a diagnosis and/or symptoms (N = 541). Participants identify as a woman and are between the ages of 15 and 44. A comparison of women with a diagnosis of a chronic physical condition and those without a diagnosis will be conducted to explore differences in depression and anxiety symptoms between women with and without a chronic medical diagnosis. The impact race, SES, and occupation will also be addressed in relation to anxiety and/or depression in women of reproductive age. This study will further the understanding of the relationship between mental illness in women of reproductive age with chronic medical conditions. The results of this study will have implications for the integration of mental health care in women’s health centers and perhaps training of clinicians and physicians providing psychological and medical care to women of reproductive age.

Keywords: mental health, physical health, reproductive age, women

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Authors: Eryati Darwin, Arina Widya Murni, Adnil Edwin Nurdin

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Background: Functional dyspepsia (FD) is a highly prevalent and heterogeneous disorder. Most patients with FD complain of symptoms related to the intake of meals. Psychological stress may promote peptic ulcer and had an effect on ulcers associated Hp, and may also trigger worsen symptoms in inflammatory disorders of the gastrointestinal. Cells in mucosal gastric stimulate the production of several cytokines, which might associated with Helicobacter pylori infection. The cascade of biological events leading to stress-induced FD remains poorly understood. Aim of Study: To determine the prion-flammatory cytokine IL-6, and Helicobacter pylori activity on mucosal gastric of FD and their association with psychological stress. Methods: The subjects of this study were dyspeptic patients who visited M. Djamil General Hospital and in two Community Health Centers in Padang. On the basis of the stress index scale to identify psychological stress by using Depression Anxiety and Stress Scale (DASS 42), subjects were divided into two groups of 20 each, stress groups and non-stress groups. All diagnoses were confirmed by review of cortisol and esophagogastroduodenoscopy reports. Gastric biopsy samples and peripheral blood were taken during diagnostic procedures. Immunohistochemistry methods were used to determine the expression of IL-6 and Hp in gastric mucosal. The data were statistically analyzed by univariate and bivariate analysis. All procedures of this study were approved by Research Ethics Committee of Medical Faculty Andalas University. Results: In this study, we enrolled 40 FD patients (26 woman and 14 men) in range between 35-56 years old. Cortisol level of blood FD patients as parameter of stress hormone which taken in the morning was significantly higher in stress group than non-stress group. The expression of IL-6 in gastric mucosa was significantly higher in stress group in compared to non-stress group (p<0,05). Helicobacter pylori activity in gastric mucosal in stress group were significantly higher than non-stress group. Conclusion: The present study showed that psychological stress can induce gastric mucosal inflammation and increase of Helicobacter pylori activity.

Keywords: functional dyspepsia, Helicobacter pylori, interleukin-6, psychological stress

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

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A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: bacteria chromosome, bacterial identification, sequence, primer generation

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Authors: H. A. Algahtani, A. S. Khan, O. Alzahrani, N. Hussein, M. A. Khan, Loudhi Y. I. Soliman

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Objective: To report on the Saudi experience (developing country) of neurological complications from bariatric surgery. The literature on the subject is reviewed. Method: This is a cross sectional study done in King Abdul Aziz Medical City Jeddah, WR, where we reviewed all charts of the patients who underwent bariatric surgery between January 1st, 2009 to December 31st , 2014. Personal and clinical data including age, sex, BMI, comorbidities, type of procedure, duration of stay in hospital, complications and postoperative follow up were collected. In addition follow up visit and remote complication if present were collected. All patients with neurological complications were reviewed in details including their clinical examination, laboratory and imaging results, treatment and prognosis. This report is essentially descriptive with no statistical analysis performed. Results: Fifteen cases were collected in this study (3%). Axonal polyneuropathy was the most frequent neurological complica¬tion, but cases of Wernicke syndrome, vitamin B12 deficiency, Guillain-Barre syndrome and cupper deficiency were also identified. Fourteen patients (93.3%) had full recovery from the neurological signs and symptoms but unfortunately one patient died. Conclusion: Bariatric surgery, a procedure that is continuously increasing in popularity, is not free of potential neurological complications. A clear education, guidelines and follow-up program should be planned and practiced. Facts should be clearly presented to the individual undergoing this type of surgery. Although a clear cause-effect relation cannot be established for the present cases, the cumulative literature on the subject makes it important to warn the patient of the potential risks of this procedure.

Keywords: bariatric surgery, neurological complications, neuropathy, Wenicke syndrome

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: Animish Jain

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This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

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Authors: Martyna Ekiert, Natalia Grzechnik, Joanna Karbowniczek, Urszula Stachewicz, Andrzej Mlyniec

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Tendon grafting is a common procedure performed to treat tendon rupture. Before the surgical procedure, tissues intended for grafts (i.e., Achilles tendon) are stored in ultra-low temperatures for a long time and also may be subjected to unfavorable conditions, such as repetitive freezing (F) and thawing (T). Such storage protocols may highly influence the graft mechanical properties, decrease its functionality and thus increase the risk of complications during the transplant procedure. The literature reports on the influence of multiple F/T cycles on internal structure and mechanical properties of tendons stay inconclusive, confirming and denying the negative influence of multiple F/T at the same time. An inconsistent research methodology and lack of clear limit of F/T cycles, which disqualifies tissue for surgical graft purposes, encouraged us to investigate the issue of multiple F/T cycles by the mean of biomechanical tensile tests supported with Scanning Electron Microscope (SEM) imaging. The study was conducted on male bovine Achilles tendon-derived from the local abattoir. Fresh tendons were cleaned of excessive membranes and then sectioned to obtained fascicle bundles. Collected samples were randomly assigned to 6 groups subjected to 1, 2, 4, 6, 8 and 12 cycles of freezing-thawing (F/T), respectively. Each F/T cycle included deep freezing at -80°C temperature, followed by thawing at room temperature. After final thawing, thin slices of the side part of samples subjected to 1, 4, 8 and 12 F/T cycles were collected for SEM imaging. Then, the width and thickness of all samples were measured to calculate the cross-sectional area. Biomechanical tests were performed using the universal testing machine (model Instron 8872, INSTRON®, Norwood, Massachusetts, USA) using a load cell with a maximum capacity of 250 kN and standard atmospheric conditions. Both ends of each fascicle bundle were manually clamped in grasping clamps using abrasive paper and wet cellulose wadding swabs to prevent tissue slipping while clamping and testing. Samples were subjected to the testing procedure including pre-loading, pre-cycling, loading, holding and unloading steps to obtain stress-strain curves for representing tendon stretching and relaxation. The stiffness of AT fascicles bundle samples was evaluated in terms of modulus of elasticity (Young’s modulus), calculated from the slope of the linear region of stress-strain curves. SEM imaging was preceded by chemical sample preparation including 24hr fixation in 3% glutaraldehyde buffered with 0.1 M phosphate buffer, washing with 0.1 M phosphate buffer solution and dehydration in a graded ethanol solution. SEM images (Merlin Gemini II microscope, ZEISS®) were taken using 30 000x mag, which allowed measuring a diameter of collagen fibrils. The results confirm a decrease in fascicle bundles Young’s modulus as well as a decrease in the diameter of collagen fibrils. These results confirm the negative influence of multiple F/T cycles on the mechanical properties of tendon tissue.

Keywords: biomechanics, collagen, fascicle bundles, soft tissue

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Authors: G. R. Khaliullina, S. L. Blashkova, I. G. Mustafin

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The article presents the results of a study involving 97 patients with different types of orthodontic pathology. Immunological examination of patients included determination of the level of α-defensin and cytokine IL-1β in mixed saliva. The study showed that the level of α-defensin serves as a diagnostic marker for determining the therapeutic measures in the treatment of inflammatory processes in periodontal tissues. Α-defensins exhibit immunomodulating and antimicrobial activity during inflammatory processes and play an important role in the regulation of the pathology of periodontal disease. The obtained data allowed the development of an algorithm for diagnosis and the implementation of immunomodulating therapy in the treatment of periodontal diseases in orthodontic patients.

Keywords: α-difensin, cytokine, orthodontic treatment, periodontal disease, periodontal pathogens

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Authors: Chongyang Ye, Rong Liu

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Elastic compression stockings (ECSs) have been widely applied in prophylaxis and treatment of chronic venous insufficiency of lower extremities. The medical function of ECS is to improve venous return and increase muscular pumping action to facilitate blood circulation, which is largely determined by the complex interaction between the ECS and lower limb tissues. Understanding the mechanical transmission of ECS along the skin surface, deeper tissues, and vascular system is essential to assess the effectiveness of the ECSs. In this study, a three-dimensional (3D) finite element (FE) model of the leg-ECS system integrated with a 3D fluid-solid interaction (FSI) model of the leg-vein system was constructed to analyze the biomechanical properties of veins and soft tissues under different ECS compression. The Magnetic Resonance Imaging (MRI) of the human leg was divided into three regions, including soft tissues, bones (tibia and fibula) and veins (peroneal vein, great saphenous vein, and small saphenous vein). The ECSs with pressure ranges from 15 to 26 mmHg (Classes I and II) were adopted in the developed FE-FSI model. The soft tissue was assumed as a Neo-Hookean hyperelastic model with the fixed bones, and the ECSs were regarded as an orthotropic elastic shell. The interfacial pressure and stress transmission were simulated by the FE model, and venous hemodynamics properties were simulated by the FSI model. The experimental validation indicated that the simulated interfacial pressure distributions were in accordance with the pressure measurement results. The developed model can be used to predict interfacial pressure, stress transmission, and venous hemodynamics exerted by ECSs and optimize the structure and materials properties of ECSs design, thus improving the efficiency of compression therapy.

Keywords: elastic compression stockings, fluid-solid interaction, tissue and vein properties, prediction

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Authors: Shammael Selorfia

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The Quality improvement project aimed to improve junior doctors and nurses’ knowledge and confidence in diagnosing and managing delirium on inpatient surgical wards in a tertiary hospital. The study aimed to develop a standardised assessment and management checklist for all staff working with patients who were presenting with signs of delirium. The aim of the study was to increase confidence of staff at dealing with delirium and improve the quality of referrals that were being sent to the Mental Health Liaison team over a 6-month period. A significant proportion of time was being spent by the Mental Health Liaison triage nurses on referrals for delirium. Data showed 28% of all delirium referrals from surgical teams were being closed at triage reflecting a poor standard of quality of those referrals. A qualitative survey of junior doctors in 6 surgical specialties in a UK tertiary hospital was conducted. These specialties include general surgery, vascular, plastic, urology, neurosurgery, and orthopaedics. The standardised checklist was distributed to all surgical wards. A comparison was made between the Mental health team caseload of delirium before intervention was compared and after. A Qualitative survey at end of 3-month cycle and compare overall caseload on Mental Health Liaison team to pre-QIP data with aim to improve quality of referrals and reduce workload on Mental Health Liaison team. At the end of the project cycle, we demonstrated an improvement in the quality of referrals with a decrease in the percentage of referrals being closed at triage by 8%. Our surveys also indicated an increase in the knowledge of official trust delirium guidelines and confidence at managing the patients. This project highlights that a new approach to delirium using multi-component interventions is needed, where the diagnosis of delirium is shared amongst medical and nursing staff, and everyone plays role in management. The key is improving awareness of delirium and encouraging the use of recognized diagnostic tools and official guidelines. Recommendations were made to the trust on how to implement a long-lasting change.

Keywords: delirium, surgery, quality, improvement

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Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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Authors: N. Al Khashan, H. Al Shammari, W. Al Bahli

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Patients who are eligible to receive treatment at the National Guard Health Affairs (NGHA), Saudi Arabia will typically have four medical record numbers (MRN), one in each of the geographical areas. More hospitals and primary healthcare facilities in other geographical areas will launch soon which means more MRNs. When patients own four MRNs, this will cause major drawbacks in patients’ quality of care such as creating new medical files in different regions for relocated patients and using referral system among regions. Consequently, the access to a patient’s medical record from other regions and the interoperability of health information between the four hospitals’ information system would be challenging. Thus, there is a need to unify medical records among these five facilities. As part of the effort to increase the quality of care, a new Hospital Information Systems (HIS) was implemented in all NGHA facilities by the end of 2016. NGHA’s plan is put to be aligned with the Saudi Arabian national transformation program 2020; whereby 70% citizens and residents of Saudi Arabia would have a unified medical record number that enables transactions between multiple Electronic Medical Records (EMRs) vendors. The aim of the study is to explore the plan, the challenges and barriers of unifying the 4 MRNs into one Enterprise Patient Identifier (EPI) in NGHA hospitals by December 2018. A descriptive study methodology was used. A journey map and a project plan are created to be followed by the project team to ensure a smooth implementation of the EPI. It includes the following: 1) Approved project charter, 2) Project management plan, 3) Change management plan, 4) Project milestone dates. Currently, the HIS is using the regional MRN. Therefore, the HIS and all integrated health care systems in all regions will need modification to move from MRN to EPI without interfering with patient care. For now, the NGHA have successfully implemented an EPI connected with the 4 MRNs that work in the back end in the systems’ database.

Keywords: consumer health, health informatics, hospital information system, universal medical record number

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Authors: Vijaya Yuvaram Singh V M, Kameshwar Rao J V

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The challenge with development of neural network based methods for medical is the availability of data. Anatomical landmark detection in the medical domain is a process to find points on the x-ray scan report of the patient. Most of the time this task is done manually by trained professionals as it requires precision and domain knowledge. Traditionally object detection based methods are used for landmark detection. Here, we utilize reinforcement learning and query based method to train a single agent capable of detecting multiple landmarks. A deep Q network agent is trained to detect single and multiple landmarks present on hip and shoulder from x-ray scan of a patient. Here a single agent is trained to find multiple landmark making it superior to having individual agents per landmark. For the initial study, five images of different patients are used as the environment and tested the agents performance on two unseen images.

Keywords: reinforcement learning, medical landmark detection, multi target detection, deep neural network

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Authors: Erin Micali, Katerina Tolstikova, Cheryl Maykel, Elizabeth Harwood

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Female ASD is seldomly studied separately from males. Further, females with ASD are disproportionately underrepresented in the research at a rate of 3:1 (male to female). As such, much of the current understanding about female rigid repetitive behaviors (RRBs) stems from research’s understanding of male RRBs. This can be detrimental to understanding female ASD because this understanding of female RRBs largely discounts female camouflaging and the possibility that females present their autistic symptoms differently. Current literature suggests that females with ASD engage in fewer RRBs than males with ASD and when females do engage in RRBs, they are likely to engage in more subtle, less overt obsessions and repetitive behaviors than males. Method: The current study utilized a mixed methods research design to identify the type and frequency of RRBs that females with ASD engaged in by using a cross-sectional design. The researcher recruited only females to be part of the present study with the criteria they be at least age six and not have co-occurring cognitive impairment. Results: The researcher collected previous testing data (Autism Diagnostic Interview-Revised (ADI-R), Child or Adolescent/Adult Sensory Profile-2, Autism/ Empathy Quotient, Yale Brown Obsessive Compulsive Checklist, Rigid Repetitive Behavior Checklist (evaluator created list), and demographic questionnaire) from 25 total participants. The participants ages ranged from six to 52. The participants were 96% Caucasion and 4% Latin American. Qualitative analysis found the current participant pool engaged in six RRB themes including repetitive behaviors, socially restrictive behaviors, repetitive speech, difficulty with transition, obsessive behaviors, and restricted interests. The current dataset engaged in socially restrictive behaviors and restrictive interests most frequently. Within the main themes 40 subthemes were isolated, defined, and analyzed. Further, preliminary quantitative analysis was run to determine if age impacted camouflaging behaviors and overall presentation of RRBs. Within this dataset this was not founded. Further qualitative data will be run to determine if this dataset engaged in more overt or subtle RRBs to confirm or rebuff previous research. The researcher intends to run SPSS analysis to determine if there was statistical difference between each RRB theme and overall presentation. Secondly, each participant will be analyzed for presentation of RRB, age, and previous diagnoses. Conclusion: The present study aimed to assist in diagnostic clarity. This was achieved by collecting data from a female only participant pool across the lifespan. Current data aided in clarity of the type of RRBs engage in. A limited sample size was a barrier in this study.

Keywords: autism spectrum disorder, camouflaging, rigid repetitive behaviors, gender disparity

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Authors: Nurul Azmawati Mohamed, Zarini Ismail, Shalinawati Ramli, Nurul Hayati Chamhuri, Nur Syahrina Rahim, K. Omar

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Choosing a career is one of the most important decisions in our life. A right career leads a person to grow with that career and achieve success through the decision. Thus, career suitability assessment is important to help individuals to understand how a variety of personal attributes can impact their potential success and satisfaction with different career options and work environments. Some career needs specific personality trait that relates to attributes of job requirements and commitments. For medicine, being caring, approachable, inquisitive, able to listen and understand patients’ pain, anxiety and sorrow are important. The aim of this study was to evaluate the career suitability of pre-clinical students. This was a cross sectional study conducted among pre-clinical medical students in Universiti Sains Islam Malaysia. 'Sidek Career Interest Inventory’ was used to assess the students’ suitability for the course. This instrument had been validated locally to suit the local social and cultural context. It assessed the students’ personality trait based on Holland’s theory and their interests. For students to pursue in the medical course, two main personality trait are believed to be essential namely investigative and social trait personalities. Some of the characteristics of investigative trait are analytical, rational, intellectual and curious, while the characteristics of social trait personality include empathy, friendly, understanding and accommodating. The score for each personality trait were categorized as low (0-3.99), moderate (4-6.99) and high (7-10). A total of 81 pre-clinical medical students were included in this study. About two third (93.8%) of them were female and all of them are from 20 to 21 of age. Approximately, half of the students (47.5%) scored high and another 46.3% scored moderate for investigative trait. For social trait, only 13.8% scored high while 31.3% scored moderate. Only 12.5% (10) students had high scores for both investigative and social traits. Most of the pre-clinical medical students scored high in the investigative sections, however their social values were inadequate (low scores). For them to become good medical doctors, they should be good in both investigative and social skills to enhance their suitability for this career. Therefore, there is a need to nurture these medical students with appropriate social values and soft skills.

Keywords: career suitability, career interest, medical students, personality trait

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Authors: Mahdieh Farzin Asanjan, Erkan Unal Mumcuoglu

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Mitochondria are cytoplasmic organelles of the cell, which have a significant role in the variety of cellular metabolic functions. Mitochondria act as the power plants of the cell and are surrounded by two membranes. Significant morphological alterations are often due to changes in mitochondrial functions. A powerful technique in order to study the three-dimensional (3D) structure of mitochondria and its alterations in disease states is Electron microscope tomography. Detection of mitochondria in electron microscopy images due to the presence of various subcellular structures and imaging artifacts is a challenging problem. Another challenge is that each image typically contains more than one mitochondrion. Hand segmentation of mitochondria is tedious and time-consuming and also special knowledge about the mitochondria is needed. Fully automatic segmentation methods lead to over-segmentation and mitochondria are not segmented properly. Therefore, semi-automatic segmentation methods with minimum manual effort are required to edit the results of fully automatic segmentation methods. Here two editing tools were implemented by applying spline surface dragging and interactive live-wire segmentation tools. These editing tools were applied separately to the results of fully automatic segmentation. 3D extension of these tools was also studied and tested. Dice coefficients of 2D and 3D for surface dragging using splines were 0.93 and 0.92. This metric for 2D and 3D for live-wire method were 0.94 and 0.91 respectively. The root mean square symmetric surface distance values of 2D and 3D for surface dragging was measured as 0.69, 0.93. The same metrics for live-wire tool were 0.60 and 2.11. Comparing the results of these editing tools with the results of automatic segmentation method, it shows that these editing tools, led to better results and these results were more similar to ground truth image but the required time was higher than hand-segmentation time

Keywords: medical image segmentation, semi-automatic methods, transmission electron microscopy, surface dragging using splines, live-wire

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Authors: Karolina Wieczorek, Sophie Wiliams

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Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

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Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

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Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The RMSE between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition

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Authors: Farzad Yavari, Hamid Chegini, Saeed Lotfi

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This paper reviews the comparison of Resin Rich (RR) and Vacuum Pressure Impregnation (VPI) insulation system qualities for stator bar of rotating electrical machines. Voltage endurance and tangent delta are two diagnostic tests to determine the quality of insulation systems. The paper describes the trend of dissipation factor while performing voltage endurance test for different stator bar samples made with RR and VPI insulation system methods. Some samples were made with the same strands and insulation thickness but with different main wall material to prove the influence of insulation system methods on stator bar quality. Also, some of the samples were subjected to voltage at the temperature of their insulation class, and their dissipation factor changes were measured and studied.

Keywords: VPI, resin rich, insulation, stator bar, dissipation factor, voltage endurance

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Authors: S. Kurian, S. Satpathy, S. K. Gupta, S. Arya, D. K. Sharma

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Advances in the use of health care technology have resulted in increased adverse events (AEs) related to the use of medical devices. The study focused on the existing reporting systems. This study was conducted in a tertiary care public sector hospital. Devices included Syringe infusion pumps, Cardiac monitors, Pulse oximeters, Ventilators and Defibrillators. A total of 211 respondents were recruited. Interviews were held with 30 key informants. Medical records were scrutinized. Relevant statistical tests were used. Resident doctors reported maximum frequency of AEs, followed by nurses; and least by consultants. A significant association was found between the cadre of health care personnel and awareness that the patients and bystanders have a risk of sustaining AE. Awareness regarding reporting of AEs was low, and it was generally done verbally. Other critical findings are discussed in the light of the barriers to reporting, reasons for non-compliance, recording system, and so on.

Keywords: adverse events, health care technology, medical devices, public sector hospital, reporting systems

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Authors: Sushmita Roy Chowdhury, Steve Holding, Sujoy Khan

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The immunogenic responses of the lung towards the fungus Aspergillus fumigatus may range from invasive aspergillosis in the immunocompromised, fungal ball or infection within a cavity in the lung in those with structural lung lesions, or allergic bronchopulmonary aspergillosis (ABPA). Patients with asthma or cystic fibrosis are particularly predisposed to ABPA. There are consensus guidelines that have established criteria for diagnosis of ABPA, but uncertainty remains on the serologic cut-off values that would increase the diagnostic specificity of ABPA. We retrospectively analyzed 80 patients with severe asthma and evidence of peripheral blood eosinophilia ( > 500) over the last 3 years who underwent all serologic tests to exclude ABPA. Total IgE, specific IgE and specific IgG levels against Aspergillus fumigatus were measured using ImmunoCAP Phadia-100 (Thermo Fisher Scientific, Sweden). The Modified ISHAM working group 2013 criteria (obligate criteria: asthma or cystic fibrosis, total IgE > 1000 IU/ml or > 417 kU/L and positive specific IgE Aspergillus fumigatus or skin test positivity; with ≥ 2 of peripheral eosinophilia, positive specific IgG Aspergillus fumigatus and consistent radiographic opacities) was used in the clinical workup for the final diagnosis of ABPA. Patients were divided into 3 groups - definite, possible, and no evidence of ABPA. Specific IgG Aspergillus fumigatus levels were not used to assign the patients into any of the groups. Of 80 patients (males 48, females 32; mean age 53.9 years ± SD 15.8) selected for the analysis, there were 30 patients who had positive specific IgE against Aspergillus fumigatus (37.5%). 13 patients fulfilled the Modified ISHAM working group 2013 criteria of ABPA (‘definite’), while 15 patients were ‘possible’ ABPA and 52 did not fulfill the criteria (not ABPA). As IgE levels were not normally distributed, median levels were used in the analysis. Median total IgE levels of patients with definite and possible ABPA were 2144 kU/L and 2597 kU/L respectively (non-significant), while median specific IgE Aspergillus fumigatus at 4.35 kUA/L and 1.47 kUA/L respectively were significantly different (comparison of standard deviations F-statistic 3.2267, significance level p=0.040). Mean levels of IgG anti-Aspergillus fumigatus in the three groups (definite, possible and no evidence of ABPA) were compared using ANOVA (Statgraphics Centurion Professional XV, Statpoint Inc). Mean levels of IgG anti-Aspergillus fumigatus (Gm3) in definite ABPA was 125.17 mgA/L ( ± SD 54.84, with 95%CI 92.03-158.32), while mean Gm3 levels in possible and no ABPA were 18.61 mgA/L and 30.05 mgA/L respectively. ANOVA showed a significant difference between the definite group and the other groups (p < 0.001). This was confirmed using multiple range tests (Fisher's least significant difference procedure). There was no significant difference between the possible ABPA and not ABPA groups (p > 0.05). The study showed that a sizeable proportion of patients with asthma are sensitized to Aspergillus fumigatus in this part of India. A higher cut-off value of Gm3 ≥ 80 mgA/L provides a higher serologic specificity towards definite ABPA. Long-term studies would provide us more information if those patients with 'possible' APBA and positive Gm3 later develop clear ABPA, and are different from the Gm3 negative group in this respect. Serologic testing with clear defined cut-offs are a valuable adjunct in the diagnosis of ABPA.

Keywords: allergic bronchopulmonary aspergillosis, Aspergillus fumigatus, asthma, IgE level

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Authors: Mrinal Kanti Bhowmik, Usha Rani Gogoi Jr., Anjan Kumar Ghosh, Debotosh Bhattacharjee

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In the last few decades, breast thermography has achieved an average sensitivity and specificity of 90% for breast tumor detection. Breast thermography is a non-invasive, cost-effective, painless and radiation-free breast imaging modality which makes a significant contribution to the evaluation and diagnosis of patients, suspected of having breast cancer. An abnormal breast thermogram may indicate significant biological risk for the existence or the development of breast tumors. Breast thermography can detect a breast tumor, when the tumor is in its early stage or when the tumor is in a dense breast. The infrared breast thermography is very sensitive to environmental changes for which acquisition of breast thermography should be performed under strictly controlled conditions by undergoing some standard protocols. Several factors like air, temperature, humidity, etc. are there to be considered for characterizing thermal images as an imperative tool for detecting breast cancer. A detailed study of various breast thermogram acquisition protocols adopted by different researchers in their research work is provided here in this paper. After going through a rigorous study of different breast thermogram acquisition protocols, a new standard breast thermography acquisition setup is proposed here in this paper for proper and accurate capturing of the breast thermograms. The proposed breast thermogram acquisition setup is being built in the Radiology Department, Agartala Government Medical College (AGMC), Govt. of Tripura, Tripura, India. The breast thermograms are captured using FLIR T650sc thermal camera with the thermal sensitivity of 20 mK at 30 degree C. The paper is an attempt to highlight the importance of different critical parameters of breast thermography like different thermography views, patient preparation protocols, acquisition room requirements, acquisition system requirements, etc. This paper makes an important contribution by providing a detailed survey and a new efficient approach on breast thermogram capturing.

Keywords: acquisition protocol, breast cancer, breast thermography, infrared thermography

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Authors: Hao-Jun Hong, Jung-Tang Huang

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The world is gradually becoming an aging society, and with the lack of laboring forces, this phenomenon is affecting the nation’s economy growth. Although nursing centers are booming in recent years, the lack of medical resources are yet to be resolved, thus creating an innovative wearable medical device could be a vital solution. This research is focused on the design and development of a wearable device which obtains a more precise heart failure measurement than products on the market. The method used by the device is based on the sensor fusion and big data algorithm. From the test result, the modified structure of wearable device can significantly decrease the MA (Motion Artifact) and provide users a more cozy and accurate physical monitor experience.

Keywords: big data, heart failure, motion artifact, sensor fusion, wearable medical device

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Authors: L. Ramirez, E. Guillén, J. Sánchez

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Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: analytics, telemedicine, internet of things, cloud computing

Procedia PDF Downloads 313

Authors: Przemysław Adamczyk, Mirosław Wyczesany, Aleksandra Domagalik, Artur Daren, Kamil Cepuch, Piotr Błądziński, Tadeusz Marek, Andrzej Cechnicki

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The present study aimed at evaluation of neural correlates of humor comprehension impairments observed in schizophrenia. To investigate the nature of this deficit in schizophrenia and to localize cortical areas involved in humor processing we used functional magnetic resonance imaging (fMRI). The study included chronic schizophrenia outpatients (SCH; n=20), and sex, age and education level matched healthy controls (n=20). The task consisted of 60 stories (setup) of which 20 had funny, 20 nonsensical and 20 neutral (not funny) punchlines. After the punchlines were presented, the participants were asked to indicate whether the story was comprehensible (yes/no) and how funny it was (1-9 Likert-type scale). fMRI was performed on a 3T scanner (Magnetom Skyra, Siemens) using 32-channel head coil. Three contrasts in accordance with the three stages of humor processing were analyzed in both groups: abstract vs neutral stories - incongruity detection; funny vs abstract - incongruity resolution; funny vs neutral - elaboration. Additionally, parametric modulation analysis was performed using both subjective ratings separately in order to further differentiate the areas involved in incongruity resolution processing. Statistical analysis for behavioral data used U Mann-Whitney test and Bonferroni’s correction, fMRI data analysis utilized whole-brain voxel-wise t-tests with 10-voxel extent threshold and with Family Wise Error (FWE) correction at alpha = 0.05, or uncorrected at alpha = 0.001. Between group comparisons revealed that the SCH subjects had attenuated activation in: the right superior temporal gyrus in case of irresolvable incongruity processing of nonsensical puns (nonsensical > neutral); the left medial frontal gyrus in case of incongruity resolution processing of funny puns (funny > nonsensical) and the interhemispheric ACC in case of elaboration of funny puns (funny > neutral). Additionally, the SCH group revealed weaker activation during funniness ratings in the left ventro-medial prefrontal cortex, the medial frontal gyrus, the angular and the supramarginal gyrus, and the right temporal pole. In comprehension ratings the SCH group showed suppressed activity in the left superior and medial frontal gyri. Interestingly, these differences were accompanied by protraction of time in both types of rating responses in the SCH group, a lower level of comprehension for funny punchlines and a higher funniness for absurd punchlines. Presented results indicate that, in comparison to healthy controls, schizophrenia is characterized by difficulties in humor processing revealed by longer reaction times, impairments of understanding jokes and finding nonsensical punchlines more funny. This is accompanied by attenuated brain activations, especially in the left fronto-parietal and the right temporal cortices. Disturbances of the humor processing seem to be impaired at the all three stages of the humor comprehension process, from incongruity detection, through its resolution to elaboration. The neural correlates revealed diminished neural activity of the schizophrenia brain, as compared with the control group. The study was supported by the National Science Centre, Poland (grant no 2014/13/B/HS6/03091).

Keywords: communication skills, functional magnetic resonance imaging, humor, schizophrenia

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

Procedia PDF Downloads 75

Authors: Sultan Çağırıcı, Arsida Bajrami, Beyza Aslan, Hacı Ali Erdoğan, Nejla Sözer Topçular, Dilek Bozkurt, Vildan Yayla

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Objective: Corticobasal syndrome (CBS) is phenotypically characterized by asymmetric rigidity, apraxia, alien-limb phenomenon, cortical sensory loss, dystonia and myoclonus. The underlying pathologies consists of corticobasal degeneration (CBD), progressive supra nuclear palsy, Alzheimer's, Creutzfeldt-Jakob and frontotemporal degeneration. CBD is a degenerative disease with clinical symptoms related to the prominent involvement of cerebral cortex and basal ganglia. CBD is a pathological diagnosis and antemortem clinical diagnosis may change many times. In this paper, we described the clinical features and discussed a cases diagnosed with symmetric CBS because of its rarity. Case: Seventy-five-year-old woman presented with a three years history of difficulty in speaking and reading. Involuntary hand jerks and slowness of movement also had began in the last six months. In the neurological examination the patient was alert but not fully oriented. The speech was non-fluent, word finding difficulties were present. Bilateral limited upgaze, bradimimia, bilateral positive cogwheel' rigidity but prominent in the right side, postural tremor and negative myoclonus during action on the left side were detected. Receptive language was normal but expressive language and repetition were impaired. Acalculia, alexia, agraphia and apraxia were also present. CSF findings were unremarkable except for elevated protein level (75 mg/dL). MRI revealed bilateral symmetric cortical atrophy prominent in the frontoparietal region. PET showed hypometabolism in the left caudate nucleus. Conclusion: The increase of data related to neurodegenerative disorders associated with dementia, movement disorders and other findings results in an expanded range of diagnosis and transitions between clinical diagnosis. When considered the age of onset, clinical symptoms, imaging findings and prognosis of this patient, clinical diagnosis was CBS and pathologic diagnosis as probable CBD. Imaging of CBD usually consist of typical asymmetry between hemispheres. Still few cases with clinical appearance of CBD may show symmetrical cortical cerebral atrophy. It is presented this case who was diagnosed with CBD although we found symmetrical cortical cerebral atrophy in MRI.

Keywords: symmetric cortical atrophy, corticobasal degeneration, corticobasal syndrome

Procedia PDF Downloads 444