Search results for: balance in patient

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

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Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

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Authors: Rubaiat S. Ahmed, Jemer Garrido, Sergey M. Motov

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Clinical informatics (CI) enables the transformation of data into a systematic organization that improves the quality of care and the generation of positive health outcomes.Innovative technology through informatics that compiles accurate data on analgesic utilization in the emergency department can enhance pain management in this important clinical setting. We aim to establish a simplified reporting system through CI to examine and assess the analgesic prescribing practices in the EDthrough executing a U.S. federal grant project on opioid reduction initiatives. Queried data points of interest from a level-one trauma ED’s electronic medical records were used to create data sets and develop informational/visual reporting dashboards (on Microsoft Excel and Google Sheets) concerning analgesic usage across several pre-defined parameters and performance metrics using CI. The data was then qualitatively analyzed to evaluate ED analgesic prescribing trends by departmental clinicians and leadership. During a 12-month reporting period (Dec. 1, 2020 – Nov. 30, 2021) for the ongoing project, about 41% of all ED patient visits (N = 91,747) were for pain conditions, of which 81.6% received analgesics in the ED and at discharge (D/C). Of those treated with analgesics, 24.3% received opioids compared to 75.7% receiving opioid alternatives in the ED and at D/C, including non-pharmacological modalities. Demographics showed among patients receiving analgesics, 56.7% were aged between 18-64, 51.8% were male, 51.7% were white, and 66.2% had government funded health insurance. Ninety-one percent of all opioids prescribed were in the ED, with intravenous (IV) morphine, IV fentanyl, and morphine sulfate immediate release (MSIR) tablets accounting for 88.0% of ED dispensed opioids. With 9.3% of all opioids prescribed at D/C, MSIR was dispensed 72.1% of the time. Hydrocodone, oxycodone, and tramadol usage to only 10-15% of the time, and hydromorphone at 0%. Of opioid alternatives, non-steroidal anti-inflammatory drugs were utilized 60.3% of the time, 23.5% with local anesthetics and ultrasound-guided nerve blocks, and 7.9% with acetaminophen as the primary non-opioid drug categories prescribed by ED providers. Non-pharmacological analgesia included virtual reality and other modalities. An average of 18.5 ED opioid orders and 1.9 opioid D/C prescriptions per 102.4 daily ED patient visits was observed for the period. Compared to other specialties within our institution, 2.0% of opioid D/C prescriptions are given by ED providers, compared to the national average of 4.8%. Opioid alternatives accounted for 69.7% and 30.3% usage, versus 90.7% and 9.3% for opioids in the ED and D/C, respectively.There is a pressing need for concise, relevant, and reliable clinical data on analgesic utilization for ED providers and leadership to evaluate prescribing practices and make data-driven decisions. Basic computer software can be used to create effective visual reporting dashboards with indicators that convey relevant and timely information in an easy-to-digest manner. We accurately examined our ED's analgesic prescribing practices using CI through dashboard reporting. Such reporting tools can quickly identify key performance indicators and prioritize data to enhance pain management and promote safe prescribing practices in the emergency setting.

Keywords: clinical informatics, dashboards, emergency department, health informatics, healthcare informatics, medical informatics, opioids, pain management, technology

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Authors: Wei Kunkun, Cao Wanyang, Xu Yujie, Qiao Yuzhi, Liu Yingning

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The reasonable design of bus parking spaces can improve the traffic capacity of the station and reduce traffic congestion. In order to reasonably determine the number of berths at BRT (Bus Rapid Transit) stops, it is based on the actual bus rapid transit station observation data, scheduling data, and passenger flow data. Optimize the number of station berths from the perspective of optimizing the balance of supply and demand at the site. Combined with the classical capacity calculation model, this paper first analyzes the important factors affecting the traffic capacity of BRT stops by using SPSS PRO and MATLAB programming software, namely the distribution of BRT stops and the distribution of BRT stop time. Secondly, the method of calculating the number of the classic human capital management (HCM) model is optimized based on the actual passenger demand of the station, and the method applicable to the actual number of station berths is proposed. Taking Gangding Station of Zhongshan Avenue Bus Rapid Transit Corridor in Guangzhou as an example, based on the calculation method proposed in this paper, the number of berths of sub-station 1, sub-station 2 and sub-station 3 is 2, which reduces the road space of the station by 33.3% compared with the previous berth 3 of each sub-station, and returns to social vehicles. Therefore, under the condition of ensuring the passenger flow demand of BRT stations, the road space of the station is reduced, and the road is returned to social vehicles, the traffic capacity of social vehicles is improved, and the traffic capacity and efficiency of the BRT corridor system are improved as a whole.

Keywords: urban transportation, bus rapid transit station, HCM model, capacity, number of berths

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Authors: Zarabizan Zakaria, Syuhaida Ismail, Aminah Md. Yusof

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Project management process starts from the planning stage up to the stage of completion (handover of buildings, preparation of the final accounts and the closing balance). This process is not easy to implement efficiently and effectively. The issue of delays in construction is a major problem for construction projects. These delays have been blamed mainly on inefficient traditional construction practices that continue to dominate the current industry. This is due to several factors, such as environments of construction technology, sophisticated design and customer demands that are constantly changing and influencing, either directly or indirectly, the practice of management. Among the identified influences are physical environment, social environment, information environment, political and moral atmosphere. Therefore, this paper is emerged to determine the problem and issues in the final account closing in construction projects, and it establishes the need to embrace Supply Chain Management (SCM) and then elucidates the need and strategies for the development of a delay reduction framework. At the same time, this paper provides effective measures to avoid or at least reduce the delay to the optimum level. Allowing problems in the closure declaration to occur without proper monitoring and control can leave negative impact on the cost and time of delivery to the end user. Besides, it can also affect the reputation or image of the agency/department that manages the implementation of a contract and consequently may reduce customer's trust towards the agencies/departments. It is anticipated that the findings reported in this paper could address root delay contributors and apply SCM tools for their mitigation for the better development of construction project.

Keywords: final account closing, construction project, construction delay, supply chain management

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Authors: Otu Otu Akanu

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The nexus between migration, national security, and human rights has become increasingly complex, particularly within Nigeria's geopolitical landscape. This study explores how Nigeria navigates the balance between safeguarding national security and upholding human rights amidst escalating regional crises, such as conflicts in the Lake Chad Basin and the Sahel. Through a comprehensive analysis of policy frameworks, security measures, and human rights protocols, this paper critically examines the challenges and opportunities in Nigeria's approach. The study employed a multidisciplinary methodology, integrating perspectives from International Relations, Human Security Studies, and Migration Law to provide a holistic understanding of the issue. Drawing on primary data from government reports, policy documents, and interviews with key stakeholders, alongside secondary literature, the study reveals a persistent tension between security imperatives and human rights obligations. While Nigeria has made strides in enhancing its security architecture, the findings highlight significant gaps in the protection of migrants' rights, often exacerbated by external pressures and domestic political dynamics. The paper argues that a recalibration of Nigeria's security and human rights policies is imperative for achieving sustainable peace and security in the region. By offering policy recommendations rooted in international best practices, this study contributes to the ongoing discourse on migration and security in West Africa and provides a framework for other nations grappling with similar challenges. This research underscores the need for an integrated approach that transcends traditional security paradigms, advocating a more inclusive and human-centered strategy in addressing the complexities of migration and national security.

Keywords: migration, national security, human rights, Nigeria, West Africa

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Authors: Ervin Meqikukiqi

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It is difficult to assess how athletes can best modify their movements to prevent non contact ACL injuries. Speaking with an athletic trainer, physical therapist, or sports medicine specialist is a good place to start. Recent research has allowed therapists and clinicians to easily identify and target weak muscle areas (e.g., weak hips, which leads to knock-kneed landing positions) and identify ways to improve strength and thus help prevent injury. In addition, other risk factors such as reduced hamstring strength and increased joint range of motion can be further assessed by a physical therapist or athletic trainer to improve performance-or rehabilitation efforts after an injury has occurred. Current studies also demonstrate that specific types of training, such as jump routines and learning to pivot properly, help athletes prevent ACL injuries. These types of exercises and training programs are more beneficial if athletes start when they are young. It may be optimal to integrate prevention programs during early adolescence, prior to when young athletes develop certain habits that increase the risk of an ACL injury. This is a 20 minute program designed to reduce the risk of tears of the Anterior Cruciate Ligament. It should be started at least four and preferably six weeks prior to start of competition.Ideally it is done five times per week preseason and three times per week in season.The coach or trainer must constantly observe athletes during these exercises to correct and maintain proper technique. Once the athletes understand the principles, they can monitor and coach each other. Four phases: Warm-up, Strengthening, Plyometrics, Agility and Balance.

Keywords: athletes, acl, prevention, injuries, plyoemtric, proprioception, agillity

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Authors: Amber Dhoot, Tarush Gupta, Andrea Gurr, William Jenkins, Sandro Pietrunti, Alexis Tang

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Background: The COVID-19 pandemic has driven pharmacovigilance towards a new paradigm. Nowadays, more people than ever before are recognising and reporting adverse reactions from medications, treatments, and vaccines. In the modern era, with over 3.8 billion users, social media has become the most accessible medium for people to voice their opinions and so provides an opportunity to engage with more patient-centric and accessible pharmacovigilance. However, the pharmaceutical industry has been slow to incorporate social media into its modern pharmacovigilance strategy. This project aims to make social media a more effective tool in pharmacovigilance, and so reduce drug costs, improve drug safety and improve patient outcomes. This will be achieved by firstly uncovering and categorising the barriers facing the widespread adoption of social media in pharmacovigilance. Following this, the potential opportunities of social media will be explored. We will then propose realistic, practical recommendations to make social media a more effective tool for pharmacovigilance. Methodology: A comprehensive systematic literature review was conducted to produce a categorised summary of these barriers. This was followed by conducting 11 semi-structured interviews with pharmacovigilance experts to confirm the literature review findings whilst also exploring the unpublished and real-life challenges faced by those in the pharmaceutical industry. Finally, a survey of the general public (n = 112) ascertained public knowledge, perception, and opinion regarding the use of their social media data for pharmacovigilance purposes. This project stands out by offering perspectives from the public and pharmaceutical industry that fill the research gaps identified in the literature review. Results: Our results gave rise to several key analysis points. Firstly, inadequacies of current Natural Language Processing algorithms hinder effective pharmacovigilance data extraction from social media, and where data extraction is possible, there are significant questions over its quality. Social media also contains a variety of biases towards common drugs, mild adverse drug reactions, and the younger generation. Additionally, outdated regulations for social media pharmacovigilance do not align with new, modern General Data Protection Regulations (GDPR), creating ethical ambiguity about data privacy and level of access. This leads to an underlying mindset of avoidance within the pharmaceutical industry, as firms are disincentivised by the legal, financial, and reputational risks associated with breaking ambiguous regulations. Conclusion: Our project uncovered several barriers that prevent effective pharmacovigilance on social media. As such, social media should be used to complement traditional sources of pharmacovigilance rather than as a sole source of pharmacovigilance data. However, this project adds further value by proposing five practical recommendations that improve the effectiveness of social media pharmacovigilance. These include: prioritising health-orientated social media; improving technical capabilities through investment and strategic partnerships; setting clear regulatory guidelines using multi-stakeholder processes; creating an adverse drug reaction reporting interface inbuilt into social media platforms; and, finally, developing educational campaigns to raise awareness of the use of social media in pharmacovigilance. Implementation of these recommendations would speed up the efficient, ethical, and systematic adoption of social media in pharmacovigilance.

Keywords: adverse drug reaction, drug safety, pharmacovigilance, social media

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Authors: Hojjat Mohammadi, Randall Divito, Gary J. E. Kramer

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Tunnelling and pipe jacking in very soft soils (fat clays), even with an Earth Pressure Balance tunnel boring machine (EPBM), can cause large ground displacements. In this study, the short-term and long-term ground and tunnel response is predicted for twin, pipe-jacked EPBM 3 meter diameter tunnels with a narrow pillar width. Initial modelling indicated complete closure of the annulus gap at the tail shield onto the centrifugally cast, glass-fiber-reinforced, polymer mortar jacking pipe (FRP). Numerical modelling was employed to simulate the excavation and support installation sequence, examine the ground response during excavation, confirm the adequacy of the pillar width and check the structural adequacy of the installed pipe. In the numerical models, Mohr-Coulomb constitutive model with the effect of unloading was adopted for the fat clays, while for the bedrock layer, the generalized Hoek-Brown was employed. The numerical models considered explicit excavation sequences and different levels of ground convergence prior to support installation. The well-studied excavation sequences made the analysis possible for this study on a very soft clay, otherwise, obtaining the convergency in the numerical analysis would be impossible. The predicted results indicate that the ground displacements around the tunnel and its effect on the pipe would be acceptable despite predictions of large zones of plastic behaviour around the tunnels and within the entire pillar between them due to excavation-induced ground movements.

Keywords: finite element modeling (FEM), pipe-jacked tunneling, very soft clay, EPBM

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Authors: Anuruddha Jagoda, Samiddhi Samarakoon, Anil Jasinghe

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In its simplest form, data quality can be defined as 'fitness for use' and it is a concept with multi-dimensions. Emergency Departments(ED) require information to treat patients and on the other hand it is the primary source of information regarding accidents, injuries, emergencies etc. Also, it is the starting point of various patient registries, databases and surveillance systems. This interventional study was carried out to improve data quality at the ED of the National Hospital of Sri Lanka (NHSL) by introducing an e health solution to improve data quality. The NHSL is the premier trauma care centre in Sri Lanka. The study consisted of three components. A research study was conducted to assess the quality of data in relation to selected five dimensions of data quality namely accuracy, completeness, timeliness, legibility and reliability. The intervention was to develop and deploy an electronic emergency department information system (eEDIS). Post assessment of the intervention confirmed that all five dimensions of data quality had improved. The most significant improvements are noticed in accuracy and timeliness dimensions.

Keywords: electronic health records, electronic emergency department information system, emergency department, data quality

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Authors: Z. Karakus, Z. Ozer

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Nurses are responsible for the care and treatment of individuals, as well as health maintenance and education. Medication administration is an important part of health promotion. The administration of a medicine is a common but important clinical procedure for nurses because of its complex structure. Therefore, medication errors are inevitable for nurses or nursing students. Medication errors can cause ineffective treatment, patient’s prolonged hospital stay, disablement, or death. Additionally, medication errors affect the global economy adversely by increasing health costs. Hence, preventing or decreasing of medication errors is a critical and essential issue in nursing. Nurse educators are in pursuit of new teaching methods to teach students significance of medication application. In the light of technological developments of this age, e-learning has started to be accepted as an important teaching method. E-learning is the use of electronic media and information and communication technologies in education. It has advantages such as flexibility of time and place, lower costs, faster delivery, and lower environmental impact. Students can make their own schedule and decide the learning method. This study is conducted to determine the impact of e-learning on medication administration of nursing students.

Keywords: e-learning, medication administration, nursing, nursing students

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Authors: Angela McCaskill

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Accounting graduates in most United States universities are not being adequately taught International Financial Reporting Standards (IFRS). As such they are not prepared with the knowledge and skills necessary to remain competitive in international businesses. One of the reasons behind the ill preparation is the lack of specific international accounting instruction available in the U.S. This paper explores the importance of IFRS education through the lenses of graduate accounting majors. The paper specifically explores graduate accounting major’s preparedness in IFRS based on their recent completion of a Master in Accountancy degree where IFRS had been integrated. The data for the study was collected via face-to face and telephone/Skype interviews and questionnaires. After the interview the participants also agreed to answer two supplementary questions. The participants were to determine the amounts that should be reported on the balance sheet under (1) IFRS and (2) U.S. GAAP. These questions intended to test their knowledge of both sets of standards. The sample consisted of on-line and brick and mortar university students enrolled in their graduate program during the period from spring semester 2016 to summer semester 2016. This study shows that a separate course should be devoted to teaching IFRS and convergence related issues. There is a direct correlation between the knowledge level of those students taking an IFRS course and the successful completion of the supplementary questions compared to those who only had IFRS instruction mixed into their U.S. GAAP based instruction. Students who took an international accounting course were better prepared for the IFRS conversion than those who did not have a separate course. Academically, universities need to take a deeper look into the needs of their students and do better at incorporating international standards in their curriculum.

Keywords: accounting education, global accounting standards, international accounting, IFRS and U.S. GAAP convergence, IFRS, U.S. GAAP

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Authors: Riham Barbar

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This paper studies the dynamic effects of charitable giving in a Ramsey model à la Becker and Foias (1994), such that heterogeneity is reduced to two types of agents: rich and poor. It is assumed that rich show a great concern for poor and enjoy giving. The introduction of charitable giving in this paper is inspired from the notion of Zakat (borrowed from the Islamic Economics) and is defined according to the warm-glow of Andreoni (1990). In this framework, we prove the existence of a steady state where only the patient agent holds capital. Furthermore, we show that local indetermincay appears. While moderate values of charitable-giving elasticity makes the appearance of endogenous fluctuations due to self-fulfilling expectations more likely, high values of this elasticity stabilizes endogenous fluctuations, by narrowing down the range of parameter values compatible with local indeterminacy and may rule out expectations-driven fluctuations if it exceeds certain threshold. Finally, cycles of period two emerge. However, charitable-giving makes it less likely for these cycles to emerge.

Keywords: charitable giving, warm-glow, bifurcations, heterogeneous agents, indeterminacy, self-fulfilling expectations, endogenous fluctuations

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Authors: Mona Elhelbawy, Mac Gray

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Traditional wired endoscopy is an intrusive process that requires a long flexible tube to be inserted through the patient’s mouth while intravenously sedated. Only images of the upper 4 feet of stomach, colon, and rectum can be captured, leaving the remaining 20 feet of small intestines. Wireless capsule endoscopy offers a painless, non-intrusive, efficient and effective alternative to traditional endoscopy. In wireless capsule endoscopy (WCE), ingestible vitamin-pill-shaped capsules with imaging capabilities, sensors, batteries, and antennas are designed to send images of the gastrointestinal (GI) tract in real time. In this paper, we investigate the radiation performance and specific absorption rate (SAR) of a miniature conformal capsule antenna operating at the Medical Implant Communication Service (MICS) frequency band in the human body. We perform numerical simulations using the finite element method based commercial software, high-frequency structure simulator (HFSS) and the ANSYS human body model (HBM). We also investigate the in-body channel characteristics between the implantable capsule and an external antenna placed on the surface of the human body.

Keywords: IEEE 802.15.6, MICS, SAR, WCE

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Authors: Yousif Mohamed Y. Abdallah, Eltayeb Wagi Allah Eltayeb, Mohamed E. Gar-elnabi, Mohamed Ahmed Ali

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To characterize coronary artery obstruction and related findings in ischemic heart patients using cardiac scintigraphy for the identification of myocardial ischemia, 146 patients were studied at basal conditions and also asked for fasting after night till the intravenous injection of the radiopharmaceutical. After the injection time about 15 to 20 minutes, the patient should eat a fatty meal and chocolate for the good excretion of the gall bladder, to evaluate the performance and regional wall motion of the left ventricle (LV). The results showed that the body mass index percentage in this sample was in range of 43.05 to 61.05. The number of patients who were catheter candidates were 56 with 43% and the patients that were not candidate to cathode were 74 patients with 57% of all patients. For the group of patients where type of ischemia was assessed, 29.5% of patients had reversible posterior and inferior wall, 15.1% of patients had fixed large from apex to base, 9.6% of patients had mild basal inferior wall, 4.8 % of patients had mild anterior wall, 6.2% of patients had antro-septal and 34.9% of patients had moderate ischemia.

Keywords: myocardial ischemia, myocardial scintigraphy, contrast ventriculography, coronary artery obstruction

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Mahsa Falahatpour

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Introduction: This study aims to explore how inter-observer variability in manual tumor segmentation impacts the reliability of radiomic features in non–small cell lung cancer (NSCLC). Methods: The study included twenty-three NSCLC tumors. Each patient had three tumor segmentations (VOL1, VOL2, VOL3) contoured on PET/CT scans by three radiation oncologists. Dice coefficients (DCS) were used to measure the segmentation variability. Radiomic features were extracted with 3D-slicer software, consisting of 66 features: first-order (n=15), second-order (GLCM, GLDM, GLRLM, and GLSZM) (n=33). The inter-observer variability of radiomic features was assessed using the intraclass correlation coefficient (ICC). An ICC > 0.8 indicates good stability. Results: The mean DSC of VOL1, VOL2, and VOL3 was 0.80 ± 0.04, 0.85 ± 0.03, and 0.76 ± 0.06, respectively. 92% of all extracted radiomic features were found to be stable (ICC > 0.8). The GLCM texture features had the highest stability (96%), followed by GLRLM features (90%) and GLSZM features (87%). The DSC was found to be highly correlated with the stability of radiomic features. Conclusion: The variability in inter-observer segmentation significantly impacts radiomics analysis, leading to a reduction in the number of appropriate radiomic features.

Keywords: PET/CT, radiomics, radiotherapy, segmentation, NSCLC

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Authors: Lina Vyas

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Gender gap, unfortunately, is still prevalent in the workplace around the world. In most countries, women are less likely than men to participate in the workplace. They earn considerably less than men for doing the same work and are generally expected to prioritize family obligations over work responsibilities. Women often face more conflicts while balancing the increasingly normalized roles of both worker and mother. True gender equality in the workplace is still a long way off. In Hong Kong, no less is this true. Despite the fact that female students are outnumbered by males at universities, only 55% of women are active participants in the labour market, and for those in the workforce, the gender pay gap is 22%. This structural inequality also exacerbates the issues of confronting biases at work for choosing to be employed as a mother, as well as reinforces the societal expectation of women to be the primary caregiver at home. These pressures are likely to add up for women and contribute to increased levels of work-life conflict, which may be a further barrier for the inclusion of women into the workplace. Family-friendly policies have long been thought to be an alleviator of work-life conflict through helping employees balance the demands in both work and family. Particularly, for women, this could be a facilitator of their integration into the workplace. However, little research has looked at how family-friendly policies may also have a gender differential in effect, as opposed to traditional notions of having universal efficacy. This study investigates both how and how much the gender dimension impacts work-family conflict. In addition to disentangling the reasons for gender gaps existing in work-life conflict for women, this study highlights what can be done at an organizational level to alleviate these conflicts. Most importantly, the policies recommendations derived from this study serve as an avenue for more active participation for women in the workplace and can be considered as a pathway for promoting greater gender egalitarianism and fairness in a traditionally gender-segregated society.

Keywords: family-friendly policies, Hong Kong, work-family conflict, workplace

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Authors: Doaa Hashad, Amany Elbanna, Abeer Ibrahim, Gihan Khedr

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Background: H19 is one of the long non coding RNAs (LncRNA) that is related to the progression of many diseases including cancers. This work was carried out to study the level of the long non-coding RNA; H119, in plasma of patients with gastric cancer (GC) and to assess its significance in their clinical management. Methods: A total of sixty-two participants were enrolled in the present study. The first group included thirty-two GC patients, while the second group was formed of thirty age and sex matched healthy volunteers serving as a control group. Plasma samples were used to assess H19 gene expression using real time quantitative PCR technique. Results: H19 expression was up-regulated in GC patients with positive correlation to TNM cancer stages. Conclusions: Up-regulation of H19 is closely associated with gastric cancer and correlates well with tumor staging. Convenient, efficient quantification of H19 in plasma using real time PCR technique implements its role as a potential noninvasive prognostic biomarker in gastric cancer, that predicts patient’s outcome and most importantly as a novel target in gastric cancer treatment with better performance achieved on using both CEA and H19 simultaneously.

Keywords: biomarker, gastric, cancer, LncRNA

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Authors: Elizabeth Russo, Angelica Terepka

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The present paper reviews literature examining trends among suicide, suicidal ideation, and mental illness rates in ethnic and racial minority student-athletes. While the rates of suicide amongst student athlete populations is lower than rates of suicide seen in the general student populations, there is a discrepancy amongst rates of suicide in student athletes; specifically, those identifying with racial and ethnic minority backgrounds endorse higher rates of suicidal ideation. The samples from the existing literature consisted of White, Black, Hispanic/Latinx, Asian/ Pacific Islander, Multiracial, and Native American student-athletes. Studies suggest that ethnic and racial minority students are more susceptible to suicide, depression, and other mental health concerns compared to their white counterparts. Across the literature, White student athletes appeared to have more social and academic support from fellow classmates, university administration and professors, and staff within their athletic departments. Student athletes who did not identify as White endorsed higher rates of loneliness, felt ethnically and racially underrepresented within their athletic department, and endorsed lack of appropriate medical treatment for injuries by athletic department medical staff. Additionally, non-White student athletes receive less peer support and must balance additional stressors such as discrimination in contrast to their White/non-Latinx peers. Recommendations for athletic departments and mental health providers supporting student athletes who identify as racial and ethnic minorities are discussed.

Keywords: racial and ethnic minority, suicide, student-athlete, suicidal ideation

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Authors: Mukurdipi Ray, Seema Singh

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Extrauterine endometrial stromal sarcoma (ESS) is a rare entity and typified by delayed recurrence of primary ESS. Here, we present an unusual case of uterine ESS in a woman with a history of hysterectomy. A 19-year-old girl, underwent a hysterectomy and bilateral salpingo-oophorectomy for uterine ESS 12 months ago and now after remaining disease free for nine months ago she presented with ascites along with pelvic and peritoneal mass. Intraoperatively, the large omental mass was found, and optimal cytoreduction with total omentomy (supracolic and infracolic ) total peritonectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) was offered to the patient. Final histopathology report showed the involvement of only omentum by ESS cells. Immunohistochemistry (IHC) and receptor study were done and it was positive for CD-10 and desmin and negative for CK- 7. This case highlights the rarity of extrauterine ESS in the omentum with a known history of primary uterine ESS which was treated successfully with the above-mentioned procedure. Though active and long-term surveillance is recommended to monitor for late recurrences.

Keywords: endrometrial stromal sarcoma, complete cytoreduction, hyperthermic intra peritoneal chemotherapy, total omentectomy

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Authors: Kevin Giraldo, Juan A. Gallego, Uriel Zapata, Fanny L. Casado

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Compliant mechanisms are designed to deform in a controlled manner in response to external forces, utilizing the flexibility of their components to store potential elastic energy during deformation, gradually releasing it upon returning to its original form. This article explores the design of a knee orthosis intended to assist users during stand-up motion. The orthosis makes use of a compliant mechanism to balance the user’s weight, thereby minimizing the strain on leg muscles during standup motion. The primary function of the compliant mechanism is to store and exchange potential energy, so when coupled with the gravitational potential of the user, the total potential energy variation is minimized. The design process for the semi-rigid knee orthosis involved material selection and the development of a numerical model for the compliant mechanism seen as a spring. Geometric properties are obtained through the numerical modeling of the spring once the desired stiffness and safety factor values have been attained. Subsequently, a 3D finite element analysis was conducted. The study demonstrates a strong correlation between the maximum stress in the mathematical model (250.22 MPa) and the simulation (239.8 MPa), with a 4.16% error. Both analyses safety factors: 1.02 for the mathematical approach and 1.1 for the simulation, with a consistent 7.84% margin of error. The spring’s stiffness, calculated at 90.82 Nm/rad analytically and 85.71 Nm/rad in the simulation, exhibits a 5.62% difference. These results suggest significant potential for the proposed device in assisting patients with knee orthopedic restrictions, contributing to ongoing efforts in advancing the understanding and treatment of knee osteoarthritis.

Keywords: biomechanics, complaint mechanisms, gonarthrosis, orthoses

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Authors: Hadeer Hegazy, Wael Ewieda, Ranin Soliman, Samah Elway, Asmaa Tawfik, Ragaa Sayed, Sahar Mousa

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The current healthcare system is facing major challenges in terms of cost, quality of care, and access to services. In response, the concept of value-based healthcare has emerged as a new approach to healthcare delivery. This concept puts the focus on patient values rather than on the traditional medical model of care. To achieve this, healthcare organizations must be agile and able to anticipate and respond quickly to changing needs. Agile management is essential for healthcare organizations to achieve value-based care, as it allows them to rapidly adjust their strategies to changing circumstances. Additionally, it is argued that agile management can help healthcare organizations gain a better understanding of the needs of their patients and develop better care delivery models. Besides, it can help healthcare organizations develop new services, innovate, and become more efficient. The authors provide evidence to support their argument, drawing on examples from successful value-based healthcare initiatives at children’s cancer hospital Egypt-57357. The paper offers insight into how agile management can be used to facilitate the shift towards value-based healthcare and how it can be used to maximize value in the healthcare system.

Keywords: value-based healthcare, agility in healthcare, nursing department, patients outcomes

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Authors: Jennifer Holbein, Maritza Wiedel

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Background: Aging is associated with an increased risk of falls in older adults, and as a result, falls have become public health crises. However, the incidence of falls can be reduced through healthy aging and the implementation of a regular exercise and strengthening program. Public health and healthcare professionals authorize the use of evidence‐based, exercise‐focused fall interventions, but there are major obstacles to translating and disseminating research findings into healthcare practices. The purpose of this study was to assess the feasibility of an intervention, A Matter of Balance, in terms of demand, acceptability, and implementation into current exercise programs. Subjects: Seventy-five participants from rural communities, above the age of sixty, were randomized to an intervention or attention-control of the standardized senior fitness test. Methods: Subject completes the intervention, which combines two components: (1) motivation and (2) fall-reducing physical activities with protocols derived from baseline strength and balanced assessments. Participants (n=75) took part in the program after completing baseline functional assessments as well as evaluations of their personal knowledge, health outcomes, demand, and implementation interventions. After 8-weeks of the program, participants were invited to complete follow-up assessments with results that were compared to their baseline functional analyses. Out of all the participants in the study who complete the initial assessment, approximately 80% are expected to maintain enrollment in the implemented prescription. Furthermore, those who commit to the program should show mitigation of fall risk upon completion of their final assessment.

Keywords: aging population, exercise, falls, functional assessment, healthy aging

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Authors: Jonathan A. Mikhail, Arsenio Paez

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It is not uncommon for a viral infection to cause hearing loss. Many viral infections are associated with sudden-onset, often unilateral, idiopathic sensorineural hearing loss. We conducted an exploratory study with thirty patients with pre-existing hearing loss between 50 and 64 to evaluate if COVID-19 was associated with exacerbated hearing loss. We hypothesized that hearing loss would be exacerbated by COVID-19 infection in patients with pre-existing hearing loss. A statistically significant paired T-test between pure tone averages (PTAs) at the patient’s original diagnosis and a current, updated audiometric assessment indicated a regression in hearing (p-value < .001) sensitivity following the contraction of COVID-19. Speech reception thresholds (SRTs) and word recognition scores (WRSs) were also considered, as well as the participants' gender. SRTs between each ear exhibited a statistically significant change (p-value of .002 and p-value < .001). WRSs did not show statistically significant differences (p-value of .290 and p-value of .098). A non-statistically significant Two-Way ANOVA was performed to evaluate gender’s potential role in exacerbated hearing loss and proved to be statistically insignificant (p-value of .214). This study discusses practical implications for clinical and educational pursuits in understanding COVID-19's effect on the auditory system and the need to evaluate the deadly virus further.

Keywords: audiology, COVID-19, sensorineural hearing loss, otology, auditory research

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Authors: Khawlah Al-Khalidi

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Prevalence of lower third molar impactions and angulations among Yemeni population The purpose of this study was to look into the prevalence of lower third molars in a sample of patients from Ibb University Affiliated Hospital, as well as to study and categorise their position by using Pell and Gregory classification, and to look into a possible correlation between their position and the indication for extraction. Materials and methods: This is a retrospective, observational study in which a sample of 200 patients from Ibb University Affiliated Hospital were studied, including patient record validation and orthopantomography performed in screening appointments in people aged 16 to 21. Results and discussion: Males make up 63% of the sample, while people aged 19 to 20 make up 41.2%. Lower third molars were found in 365 of the 365 instances examined, accounting for 91% of the sample under study. According to Pell and Gregory's categorisation, the most common position is IIB, with 37%, followed by IIA with 21%; less common classes are IIIA, IC, and IIIC, with 1%, 3%, and 3%, respectively. It was feasible to determine that 56% of the lower third molars in the sample were recommended for extraction during the screening consultation. Finally, there are differences in third molar location and angulation. There was, however, a link between the available space for third molar eruption and the need for tooth extraction.

Keywords: lower third molar, extraction, Pell and Gregory classification, lower third molar impaction

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Authors: Shaoyi Lu

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Background: Traditional Chinese medicine has been used to treat stroke, which is a major cause of morbidity and mortality. There is, however, no clear agreement about the optimal timing, population, efficacy, and predictive prognosis factors of traditional Chinese medicine supplemental therapy. Method: In this study, we used a retrospective analysis with data collection from stroke patients in Stroke Registry In Chang Gung Healthcare System (SRICHS). Stroke patients who received traditional Chinese medicine consultation in neurology ward of Keelung Chang Gung Memorial Hospital from Jan 2010 to Dec 2014 were enrolled. Clinical profiles including the neurologic deficit, activities of daily living and other basic characteristics were analyzed. Through propensity score matching, we compared the NIHSS and Barthel index before and after the hospitalization, and applied with subgroup analysis, and adjusted by multivariate regression method. Results: Totally 115 stroke patients were enrolled with experiment group in 23 and control group in 92. The most important factor for prognosis prediction were the scores of National Institutes of Health Stroke Scale and Barthel index right before the hospitalization. Traditional Chinese medicine intervention had no statistically significant influence on the neurological deficit of acute stroke patients, and mild negative influence on daily activity performance of acute hemorrhagic stroke patient. Conclusion: Efficacy of traditional Chinese medicine as a supplemental therapy for acute stroke patients was controversial. The reason for this phenomenon might be complex and require more research to comprehend. Key words: traditional Chinese medicine, acupuncture, Stroke, NIH stroke scale, Barthel index, predictive factor. Method: In this study, we used a retrospective analysis with data collection from stroke patients in Stroke Registry In Chang Gung Healthcare System (SRICHS). Stroke patients who received traditional Chinese medicine consultation in neurology ward of Keelung Chang Gung Memorial Hospital from Jan 2010 to Dec 2014 were enrolled. Clinical profiles including the neurologic deficit, activities of daily living and other basic characteristics were analyzed. Through propensity score matching, we compared the NIHSS and Barthel index before and after the hospitalization, and applied with subgroup analysis, and adjusted by multivariate regression method. Results: Totally 115 stroke patients were enrolled with experiment group in 23 and control group in 92. The most important factor for prognosis prediction were the scores of National Institutes of Health Stroke Scale and Barthel index right before the hospitalization. Traditional Chinese medicine intervention had no statistically significant influence on the neurological deficit of acute stroke patients, and mild negative influence on daily activity performance of acute hemorrhagic stroke patient. Conclusion: Efficacy of traditional Chinese medicine as a supplemental therapy for acute stroke patients was controversial. The reason for this phenomenon might be complex and require more research to comprehend.

Keywords: traditional Chinese medicine, complementary and alternative medicine, stroke, acupuncture

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Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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