Search results for: medical diagnosis
4768 Application of Local Mean Decomposition for Rolling Bearing Fault Diagnosis Based On Vibration Signals
Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine
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Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.Keywords: fault diagnosis, condition monitoring, local mean decomposition, rolling element bearing, vibration analysis
Procedia PDF Downloads 3894767 The Importance of Development in Laboratory Diagnosis at the Intersection
Authors: Agus Sahri, Cahya Putra Dinata, Faishal Andhi Rokhman
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Intersection is a critical area on a highway which is a place of conflict points and congestion due to the meeting of two or more roads. Conflicts that occur at the intersection include diverging, merging, weaving, and crossing. To deal with these conflicts, a crossing control system is needed, at a plot of intersection there are two control systems namely signal intersections and non-signalized intersections. The control system at a plot of intersection can affect the intersection performance. In Indonesia there are still many intersections with poor intersection performance. In analyzing the parameters to measure the performance of a plot of intersection in Indonesia, it is guided by the 1997 Indonesian Road Capacity Manual. For this reason, this study aims to develop laboratory diagnostics at plot intersections to analyze parameters that can affect the performance of an intersection. The research method used is research and development. The laboratory diagnosis includes anamnesis, differential diagnosis, inspection, diagnosis, prognosis, specimens, analysis and sample data analysts. It is expected that this research can encourage the development and application of laboratory diagnostics at a plot of intersection in Indonesia so that intersections can function optimally.Keywords: intersection, the laboratory diagnostic, control systems, Indonesia
Procedia PDF Downloads 1764766 Online Electric Current Based Diagnosis of Stator Faults on Squirrel Cage Induction Motors
Authors: Alejandro Paz Parra, Jose Luis Oslinger Gutierrez, Javier Olaya Ochoa
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In the present paper, five electric current based methods to analyze electric faults on the stator of induction motors (IM) are used and compared. The analysis tries to extend the application of the multiple reference frames diagnosis technique. An eccentricity indicator is presented to improve the application of the Park’s Vector Approach technique. Most of the fault indicators are validated and some others revised, agree with the technical literatures and published results. A tri-phase 3hp squirrel cage IM, especially modified to establish different fault levels, is used for validation purposes.Keywords: motor fault diagnosis, induction motor, MCSA, ESA, Extended Park´s vector approach, multiparameter analysis
Procedia PDF Downloads 3424765 The Role of Genetic Markers in Prostate Cancer Diagnosis and Treatment
Authors: Farman Ali, Asif Mahmood
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The utilization of genetic markers in prostate cancer management represents a significant advance in personalized medicine, offering the potential for more precise diagnosis and tailored treatment strategies. This paper explores the pivotal role of genetic markers in the diagnosis and treatment of prostate cancer, emphasizing their contribution to the identification of individual risk profiles, tumor aggressiveness, and response to therapy. By integrating current research findings, we discuss the application of genetic markers in developing targeted therapies and the implications for patient outcomes. Despite the promising advancements, challenges such as accessibility, cost, and the need for further validation in diverse populations remain. The paper concludes with an outlook on future directions, underscoring the importance of genetic markers in revolutionizing prostate cancer care.Keywords: prostate cancer, genetic markers, personalized medicine, BRCA1 and BRCA2
Procedia PDF Downloads 564764 A Unique Immunization Card for Early Detection of Retinoblastoma
Authors: Hiranmoyee Das
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Aim. Due to late presentation and delayed diagnosis mortality rate of retinoblastoma is more than 50% in developing counties. So to facilitate the diagnosis, to decrease the disease and treatment burden and to increase the disease survival rate, an attempt was made for early diagnosis of Retinoblastoma by including fundus examination in routine immunization programs. Methods- A unique immunization card is followed in a tertiary health care center where examination of pupillary reflex is made mandatory in each visit of the child for routine immunization. In case of any abnormality, the child is referred to the ophthalmology department. Conclusion- Early detection is the key in the management of retinoblastoma. Every child is brought to the health care system at least five times before the age of 2 years for routine immunization. We should not miss this golden opportunity for early detection of retinoblastoma.Keywords: retinoblastoma, immunization, unique, early
Procedia PDF Downloads 1904763 The Role of Critical Thinking in Disease Diagnosis: A Comprehensive Review
Authors: Mohammad Al-Mousawi
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This academic article explores the indispensable role of critical thinking in the process of diagnosing diseases. Employing a multidisciplinary approach, we delve into the cognitive skills and analytical mindset that clinicians, researchers, and healthcare professionals must employ to navigate the complexities of disease identification. By examining the integration of critical thinking within the realms of medical education, diagnostic decision-making, and technological advancements, this article aims to underscore the significance of cultivating and applying critical thinking skills in the ever-evolving landscape of healthcare.Keywords: critical thinking, medical education, diagnostic decision-making, fostering critical thinking
Procedia PDF Downloads 634762 Calculating Ventricle’s Area Based on Clinical Dementia Rating Values on Coronal MRI Image
Authors: Retno Supriyanti, Ays Rahmadian Subhi, Yogi Ramadhani, Haris B. Widodo
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Alzheimer is one type of disease in the elderly that may occur in the world. The severity of the Alzheimer can be measured using a scale called Clinical Dementia Rating (CDR) based on a doctor's diagnosis of the patient's condition. Currently, diagnosis of Alzheimer often uses MRI machine, to know the condition of part of the brain called Hippocampus and Ventricle. MRI image itself consists of 3 slices, namely Coronal, Sagittal and Axial. In this paper, we discussed the measurement of the area of the ventricle especially in the Coronal slice based on the severity level referring to the CDR value. We use Active Contour method to segment the ventricle’s region, therefore that ventricle’s area can be calculated automatically. The results show that this method can be used for further development in the automatic diagnosis of Alzheimer.Keywords: Alzheimer, CDR, coronal, ventricle, active contour
Procedia PDF Downloads 2574761 Integrating AI into Breast Cancer Diagnosis: Aligning Perspectives for Effective Clinical Practice
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
Procedia PDF Downloads 464760 Nontuberculous Mycobacterium Infection – Still An Important Disease Among People With Late HIV Diagnosis
Authors: Jakub Młoźniak, Adam Szymański, Gabriela Stondzik, Dagny Krankowska, Tomasz Mikuła
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Nontuberculous mycobacteria (NTM) are bacterial species that cause diversely manifesting diseases mainly in immunocompromised patients. In people with HIV, NTM infection is an AIDS-defining disease and usually appears when the lymphocyte T CD4 count is below 50 cells/μl. The usage of antiretroviral therapy has decreased the prevalence of NTM among people with HIV, but the disease can still be observed especially among patients with late HIV diagnosis. Common presence in environment, human colonization, clinical similarity with tuberculosis and slow growth on culture makes NTM especially hard to diagnose. The study aimed to analyze the epidemiology and clinical course of NTM among patients with HIV. This study included patients with NTM and HIV admitted to our department between 2017 and 2023. Medical records of patients were analyzed and data on age, sex, median time from HIV diagnosis to identification of NTM infection, median CD4 count at NTM diagnosis, methods of determining NTM infection, type of species of mycobacteria identified, clinical symptoms and treatment course were gathered. Twenty-four patients (20 men, 4 women) with identified NTM were included in this study. Among them, 20 were HIV late presenters. The patients' median age was 40. The main symptoms which patients presented were fever, weight loss and cough. Pulmonary disease confirmed with positive cultures from sputum/bronchoalveolar lavage was present in 18 patients. M. avium was the most common species identified. M. marinum caused disseminated skin lesions in 1 patient. Out of all, 5 people were not treated for NTM caused by lack of symptoms and suspicion of colonization with mycobacterium. Concomitant tuberculosis was present in 6 patients. The median diagnostic time from HIV to NTM infections was 3.5 months. The median CD4 count at NTM identification was 69.5 cells/μl. Median NTM treatment time was 16 months but 7 patients haven’t finished their treatment yet. The most commonly used medications were ethambutol and clarithromycin. Among analyzed patients, 4 of them have died. NTM infections are still an important disease among patients who are HIV late presenters. This disease should be taken into consideration during the differential diagnosis of fever, weight loss and cough in people with HIV with lymphocyte T CD4 count <100 cells/μl. Presence of tuberculosis does not exclude nontuberculous mycobacterium coinfection.Keywords: mycobacteriosis, HIV, late presenter, epidemiology
Procedia PDF Downloads 374759 FlexPoints: Efficient Algorithm for Detection of Electrocardiogram Characteristic Points
Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk
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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression
Procedia PDF Downloads 1574758 Retrospective Study for Elective Medical Patients Evacuation of Different Diagnoses Requiring Different Approach in Oxygen Usage
Authors: Branimir Skoric
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Over the past two decades, number of international travels rose significantly in the United Kingdom and Worldwide in the shape of business travels and holiday travels as well. The fact that elderly people travel a lot, more than ever before increased the needs for medical evacuations (repatriations) back home if they fell ill abroad or had any kind of accident. This paper concerns medical evacuations of patients on the way back home to the United Kingdom (United Kingdom Residents) and their specific medical needs during short-haul or long-haul commercial scheduled flight and ground transportation to the final destination regardless whether it was hospital or usual place of residence. Particular medical need during medical evacuations is oxygen supply and it can be supplied via portable oxygen concentrator, pulse flow oxygenator or continuous free flow oxygenator depending on the main diagnosis and patient’s comorbidities. In this retrospective study, patients were divided into two groups. One group was consisted of patients suffering from cardio-respiratory diagnoses as primary illness. Another Group consisted of patients suffering from noncardiac illnesses who have other problems including any kind of physical injury. Needs for oxygen and type of supply were carefully considered in regards of duration of the flight, standard airline cabin pressure and results described in this retrospective study.Keywords: commercial flight, elderly travellers, medical evacuations, oxygen
Procedia PDF Downloads 1414757 Computer-Aided Detection of Simultaneous Abdominal Organ CT Images by Iterative Watershed Transform
Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid
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Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm
Procedia PDF Downloads 4304756 Diagnosis of Diabetes Using Computer Methods: Soft Computing Methods for Diabetes Detection Using Iris
Authors: Piyush Samant, Ravinder Agarwal
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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction
Procedia PDF Downloads 3944755 Implementation and Comparative Analysis of PET and CT Image Fusion Algorithms
Authors: S. Guruprasad, M. Z. Kurian, H. N. Suma
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Medical imaging modalities are becoming life saving components. These modalities are very much essential to doctors for proper diagnosis, treatment planning and follow up. Some modalities provide anatomical information such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-rays and some provides only functional information such as Positron Emission Tomography (PET). Therefore, single modality image does not give complete information. This paper presents the fusion of structural information in CT and functional information present in PET image. This fused image is very much essential in detecting the stages and location of abnormalities and in particular very much needed in oncology for improved diagnosis and treatment. We have implemented and compared image fusion techniques like pyramid, wavelet, and principal components fusion methods along with hybrid method of DWT and PCA. The performances of the algorithms are evaluated quantitatively and qualitatively. The system is implemented and tested by using MATLAB software. Based on the MSE, PSNR and ENTROPY analysis, PCA and DWT-PCA methods showed best results over all experiments.Keywords: image fusion, pyramid, wavelets, principal component analysis
Procedia PDF Downloads 2784754 Vegetative Materia Medica for the Women Illness in mss2999 Kitab Tibb: A Modern Medical Interpretation of a Malay Medical Manuscript
Authors: Wan Aminah Hasbullah
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The knowledge of medicine in Malay society stemmed out from the need to remedy disease process. Such knowledge came from observations by looking at the signs on the plants which signify it uses, the doctrine of signature, and also observing what kind of animal and its parts that can be used to treat the disease. Prayers (jampi and doa’) play a very important role in the therapeutic processes addressing the ethereal part of the body. In Malay medicine, prayers were said in the heart of the Malay bomoh (medicine man) when they are first approaching the diseased person, seeking the help of Allah in accurately directing his mind into making the right diagnosis and subsequently the right choice of treatment. In the making of medicine, similar rituals were religiously followed, starting from gathering the materia medica to the final concoction of the medicine. Thus, all the materia medica and the prayers in Malay medicine were gathered and documented in the medical manuscript known as MSS 2999 Kitab Tibb. For this study, a collection of vegetative materia medica which is specialized for the women illness from this manuscript will be gathered and analysed. A medical and cultural interpretation will be highlighted to see the relationship between efficacy in traditional Malay medicine as practiced in the past and the recent practice of the modern medicine.Keywords: vegetative, materia medica, woman illness, Malay medical manuscript
Procedia PDF Downloads 2444753 The Risk of Hyperglycemia Associated with Use of Dolutegravir among Adults Living with HIV in Kampala, Uganda: A Case Control Study
Authors: Daphine Namara, Jeremy I. Schwartz, Andrew K. Tusubira, Willi McFarland, Caroline Birungi, Fred C. Semitala, Martin Muddu
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Emerging evidence suggests a possible association between hyperglycemia and dolutegravir (DTG), a preferred first-line antiretroviral agent in sub-Saharan Africa (SSA). There is a need for rigorous studies to validate this association in the face of increasing DTG use and the burden of non-communicable diseases among people living with HIV (PLHIV). We conducted a case-control study to assess the risk of hyperglycemia associated with the use of DTG among PLHIV attending Mulago ISS Clinic in Kampala. Cases had hyperglycemia, while controls had no hyperglycemia, as confirmed by fasting plasma glucose and oral glucose tolerance tests. Demographic, laboratory, and clinical data were collected using interviewer-administered questionnaires and medical record abstraction. The analysis compared cases and controls on DTG use prior to diagnosis of hyperglycemia while controlling for potential confounders using multivariable logistic regression. We included 204 cases and 231 controls. In multivariable analysis, patients with prior DTG use had seven times greater odds of subsequent diagnosis of hyperglycemia compared to those who had non-DTG-based regimens (adjusted odds ratio [aOR] 7.01, 95% CI 1.96-25.09). The odds of hyperglycemia also increased with age (56 years and above vs. 18-35, aOR 12.38, 95% CI 3.79-40.50) and hypertension (aOR 5.78, 95% CI 2.53-13.21). Our study demonstrates a strong association between prior DTG exposure and subsequent diagnosis of hyperglycemia. Given the benefits of DTG, wide-scale use, and the growing burden of diabetes mellitus (DM) in SSA, there is a need for systematic screening for hyperglycemia and consideration of alternate regimens for those at risk for DM.Keywords: HIV, hyperglycemia, doluteravir, diabetes
Procedia PDF Downloads 824752 Usability Evaluation of Rice Doctor as a Diagnostic Tool for Agricultural Extension Workers in Selected Areas in the Philippines
Authors: Jerome Cayton Barradas, Rowely Parico, Lauro Atienza, Poornima Shankar
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The effective agricultural extension is essential in facilitating improvements in various agricultural areas. One way of doing this is through Information and communication technologies (ICTs) like Rice Doctor (RD), an app-based diagnostic tool that provides accurate and timely diagnosis and management recommendations for more than 80 crop problems. This study aims to evaluate the RD usability by determining the effectiveness, efficiency, and user satisfaction of RD in making an accurate and timely diagnosis. It also aims to identify other factors that affect RD usability. This will be done by comparing RD with two other diagnostic methods: visual identification-based diagnosis and reference-guided diagnosis. The study was implemented in three rice-producing areas and has involved 96 extension workers. Respondents accomplished a self-administered survey and participated in group discussions. Data collected was then subjected to qualitative and quantitative analysis. Most of the respondents were satisfied with RD and believed that references are needed in assuring the accuracy of diagnosis. The majority found it efficient and easy to use. Some found it confusing and complicated, but this is because of their unfamiliarity with RD. Most users were also able to achieve accurate diagnosis proving effectiveness. Lastly, although users have reservations, they are satisfied and open to using RD. The study also found out the importance of visual identification skills in using RD and the need for capacity development and improvement of access to RD devices. From these results, the following are recommended to improve RD usability: review and upgrade diagnostic keys, expand further RD content, initiate capacity development for AEWs, and prepare and implement an RD communication plan.Keywords: agricultural extension, crop protection, information and communication technologies, rice doctor
Procedia PDF Downloads 2464751 Robust Diagnosability of PEMFC Based on Bond Graph LFT
Authors: Ould Bouamama, M. Bressel, D. Hissel, M. Hilairet
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Fuel cell (FC) is one of the best alternatives of fossil energy. Recently, the research community of fuel cell has shown a considerable interest for diagnosis in view to ensure safety, security, and availability when faults occur in the process. The problematic for model based FC diagnosis consists in that the model is complex because of coupling of several kind of energies and the numerical values of parameters are not always known or are uncertain. The present paper deals with use of one tool: the Linear Fractional Transformation bond graph tool not only for uncertain modelling but also for monitorability (ability to detect and isolate faults) analysis and formal generation of robust fault indicators with respect to parameter uncertainties.The developed theory applied to a nonlinear FC system has proved its efficiency.Keywords: bond graph, fuel cell, fault detection and isolation (FDI), robust diagnosis, structural analysis
Procedia PDF Downloads 3594750 A New Approach of Preprocessing with SVM Optimization Based on PSO for Bearing Fault Diagnosis
Authors: Tawfik Thelaidjia, Salah Chenikher
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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approachKeywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement
Procedia PDF Downloads 4334749 Placenta Parenchymal Dysplasia: When to Depend on Color Doppler and MRI
Authors: Bernard Olumide Ewuoso, Asma Gharaibeh
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Rationale: Placental mesenchymal dysplasia (PMD) resembles molar pregnancy quite a bit. Although there have been documented live births of healthy babies, obtaining an objective diagnosis is crucial to assisting the mother in making an educated decision on what option of management she would like to explore. Prenatal invasive testing is recommended to help obtain an objective diagnosis in cases of abnormal placenta. We present a 23-year-old who, at 14 weeks, had ultrasonographic findings suggestive of placental mesenchymal dysplasia. She was offered prenatal invasive testing but declined and opted for surgical management, with a diagnosis of PMD confirmed on histopathology. There will be occasions such as this when prenatal invasive testing is declined. In these situations, careful consideration can be given to color Doppler and MRI, especially if the patient decides to keep pregnancy.Keywords: placental mesenchymal dysplasisa, molar pregnancy, prenatal invasive testing, Color doppler, MRI
Procedia PDF Downloads 114748 Being Reticent for Healing – Singularity and Non-Verbalization in Indigenous Medical Practices in Sri Lanka
Authors: Ayami Umemura
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The purpose of this paper is to examine the meaning of verbalization in clinical practice using the keywords silence and singularity. A patient's experience of illness and treatment is singular, irreplaceable, and irreproducible and ultimately cannot be compared with that of others. In his book Difference and Repetition, Gilles Deleuze positioned irreplaceable singularity as the opposite concept of particularity as a generalizable and substitutable property and matched the former with universality. He also said that singularity could not be represented because of its irreplaceable nature. Representation or verbalization is a procedure that converts an irreplaceable, idiosyncratic reality into something that can be substituted. Considering the act of verbalizing medical diagnosis based on this, it can be said that diagnosis is the practice of decontextualizing and generalizing the suffering embedded in the patient's irreplaceable life history as a disease. This paper examines the above with the key concept of the practice of "non-verbalization" in traditional medical practices in Sri Lanka. In the practice of Sri Lankan traditional medicine and the inheritance of medical knowledge and care techniques, there is a tendency to avoid verbalizing specific matters or stating them aloud. Specifically, the following should be avoided. The healer informs the patient of the name of the disease, mentions the name of the herb used in front of the patient, explains the patient's condition to the healer, and referring the names of poisonous animals, such as poisonous snakes that have been damaged. And so on. Furthermore, when passing on medical knowledge and skills, it is also possible to avoid verbalizing knowledge of medicinal herbs and medical treatment methods and explaining them verbally. In addition to the local belief that the soul of language in Sri Lanka is deeply involved in this background, Sri Lankan traditional medicine has a unique view of the human body and personality that is rooted in the singularity that appears in the relationship with the movement of celestial bodies and the supernatural realm. It can be pointed out that it is premised on the view. In other words, the “silence” in Sri Lankan indigenous medicine is the reason for emphasizing specificity. Furthermore, we can say that "non-verbalization" is a practice aimed at healing. Based on these discussions, this paper will focus on the unique relationships between practitioners and patients that become invisible due to verbalization, which is overlooked by clinical medicine, where informed consent, ensuring transparency, and audit culture is dominant. We will examine the experience of treatment and aim to relativize clinical medicine, which is based on audit cultures.Keywords: audit cultures, indigenous medicine, singularity, verbalization
Procedia PDF Downloads 774747 Artificial Neural Networks with Decision Trees for Diagnosis Issues
Authors: Y. Kourd, D. Lefebvre, N. Guersi
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This paper presents a new idea for fault detection and isolation (FDI) technique which is applied to industrial system. This technique is based on Neural Networks fault-free and Faulty behaviors Models (NNFM's). NNFM's are used for residual generation, while decision tree architecture is used for residual evaluation. The decision tree is realized with data collected from the NNFM’s outputs and is used to isolate detectable faults depending on computed threshold. Each part of the tree corresponds to specific residual. With the decision tree, it becomes possible to take the appropriate decision regarding the actual process behavior by evaluating few numbers of residuals. In comparison to usual systematic evaluation of all residuals, the proposed technique requires less computational effort and can be used for on line diagnosis. An application example is presented to illustrate and confirm the effectiveness and the accuracy of the proposed approach.Keywords: neural networks, decision trees, diagnosis, behaviors
Procedia PDF Downloads 4934746 Maximum Entropy Based Image Segmentation of Human Skin Lesion
Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam
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Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi, and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.Keywords: shannon, maximum entropy, Renyi, Tsallis entropy
Procedia PDF Downloads 4564745 Teleconsultations and The Need of Onsite Additional Medical Services
Authors: Cristina Hotoleanu
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Introduction: The recent Covid-19 pandemic accelerated the development of e-health, including telemedicine, smartphone applications, and medical wearable devices. Providing remote teleconsultations supposes challenges which may require further face-to-face medical interactions. The aim of this study was to assess the correlation between the types of teleconsultations and the need of onsite medical services (investigations and medical visits) for the diagnosis and treatment. Methods: a retrospective study including all the teleconsultations using the platform offered by a telehealth provider in Romania (Telios Care SA) between May 1, 2021- April 30, 2022, was performed. Binary data were analysed using the chi-square test with a significance level of p < 0.05. Results: out of 7163 consultations, 3961 were phone calls, 1981 were online messages, and 1221 were video calls. Onsite medical services were indicated in 3327 (46.44%) cases; the onsite investigations or the onsite visits were recommended for 2908 patients as follows: 2326 in case of phone calls, 582 in case of online messages, none in case of video calls. Both onsite investigations and visits were indicated for 419 patients. The need for onsite additional medical services was significantly higher in the case of phone calls than in the other 2 types of teleconsultations (Chi square= 1207.06, p= 0.00001). The indication for onsite services was done mainly after teleconsultations covering medical specialties (87.34%), significantly higher than the other specialties (Chi square=914.59, p=0.00001). Teleconsultations in surgical specialties and other fields (pharmacy, dentistry, psychology, wellbeing- nutrition, fitness) resulted in 12.13%, respective less than 1%, indication for onsite investigations or visits, explained by using of video calls in most of the cases. Conclusion: a further onsite medical service was necessary in less than a half of the teleconsultations. This indication was done mainly after phone calls and teleconsultations in medical specialties. Video calls were used mostly in psychology, nutrition, and fitness teleconsultations and did not require a further onsite medical service. Other studies are necessary to assess better the types of teleconsultations and the specialties bringing the biggest benefit for the patients.Keywords: onsite medical services, phone calls, teleconsultations, telemedicine
Procedia PDF Downloads 944744 New Test Algorithm to Detect Acute and Chronic HIV Infection Using a 4th Generation Combo Test
Authors: Barun K. De
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Acquired immunodeficiency syndrome (AIDS) is caused by two types of human immunodeficiency viruses, collectively designated HIV. HIV infection is spreading globally particularly in developing countries. Before an individual is diagnosed with HIV, the disease goes through different phases. First there is an acute early phase that is followed by an established or chronic phase. Subsequently, there is a latency period after which the individual becomes immunodeficient. It is in the acute phase that an individual is highly infectious due to a high viral load. Presently, HIV diagnosis involves use of tests that do not detect the acute phase infection during which both the viral RNA and p24 antigen are expressed. Instead, these less sensitive tests detect antibodies to viral antigens which are typically sero-converted later in the disease process following acute infection. These antibodies are detected in both asymptomatic HIV-infected individuals as well as AIDS patients. Studies indicate that early diagnosis and treatment of HIV infection can reduce medical costs, improve survival, and reduce spreading of infection to new uninfected partners. Newer 4th generation combination antigen/antibody tests are highly sensitive and specific for detection of acute and established HIV infection (HIV1 and HIV2) enabling immediate linkage to care. The CDC (Center of Disease Control, USA) recently recommended an algorithm involving three different tests to screen and diagnose acute and established infections of HIV-1 and HIV-2 in a general population. Initially a 4th generation combo test detects a viral antigen p24 and specific antibodies against HIV -1 and HIV-2 envelope proteins. If the test is positive it is followed by a second test known as a differentiation assay which detects antibodies against specific HIV-1 and HIV-2 envelope proteins confirming established infection of HIV-1 or HIV-2. However if it is negative then another test is performed that measures viral load confirming an acute HIV-1 infection. Screening results of a Phoenix area population detected 0.3% new HIV infections among which 32.4% were acute cases. Studies in the U.S. indicate that this algorithm effectively reduces HIV infection through immediate treatment and education following diagnosis.Keywords: new algorithm, HIV, diagnosis, infection
Procedia PDF Downloads 4014743 Diagnosis and Treatment of Sleep Disorders
Authors: Andrew Anis Fakhrey Mosaad
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Introduction: There are many different types of sleep disorders, each with serious implications for a person's health and a large financial burden on society. Method: This review offers a framework based on the International Classification of Sleep Disorders to aid in the diagnosis and treatment of sleep disorders. Differentiating between primary and secondary insomnia is covered, along with pharmacological and nonpharmacological therapy options. Common abnormalities of the circadian rhythm are mentioned along with their therapies, such as light therapy and chronotherapy. This article discusses the identification and management of periodic limb movement disorder and restless legs syndrome. The therapy of upper airway resistance syndrome and obstructive sleep apnea are the main topics of discussion. Conclusion: The range of narcolepsy symptoms and results, as well as diagnostic procedures and treatment, are discussed. The causes, outcomes, and treatments of many types of insomnias, such as sleep terrors, somnambulism, and rapid eye movement (REM) behavior sleep disorders, are discussed.Keywords: diagnosis, treatment, sleep disorders, insomnia
Procedia PDF Downloads 504742 Development of an Interactive and Robust Image Analysis and Diagnostic Tool in R for Early Detection of Cervical Cancer
Authors: Kumar Dron Shrivastav, Ankan Mukherjee Das, Arti Taneja, Harpreet Singh, Priya Ranjan, Rajiv Janardhanan
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Cervical cancer is one of the most common cancer among women worldwide which can be cured if detected early. Manual pathology which is typically utilized at present has many limitations. The current gold standard for cervical cancer diagnosis is exhaustive and time-consuming because it relies heavily on the subjective knowledge of the oncopathologists which leads to mis-diagnosis and missed diagnosis resulting false negative and false positive. To reduce time and complexities associated with early diagnosis, we require an interactive diagnostic tool for early detection particularly in developing countries where cervical cancer incidence and related mortality is high. Incorporation of digital pathology in place of manual pathology for cervical cancer screening and diagnosis can increase the precision and strongly reduce the chances of error in a time-specific manner. Thus, we propose a robust and interactive cervical cancer image analysis and diagnostic tool, which can categorically process both histopatholgical and cytopathological images to identify abnormal cells in the least amount of time and settings with minimum resources. Furthermore, incorporation of a set of specific parameters that are typically referred to for identification of abnormal cells with the help of open source software -’R’ is one of the major highlights of the tool. The software has the ability to automatically identify and quantify the morphological features, color intensity, sensitivity and other parameters digitally to differentiate abnormal from normal cells, which may improve and accelerate screening and early diagnosis, ultimately leading to timely treatment of cervical cancer.Keywords: cervical cancer, early detection, digital Pathology, screening
Procedia PDF Downloads 1704741 Use of Machine Learning Algorithms to Pediatric MR Images for Tumor Classification
Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos
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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology
Procedia PDF Downloads 1434740 A Comparative Study on Deep Learning Models for Pneumonia Detection
Authors: Hichem Sassi
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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.Keywords: deep learning, computer vision, pneumonia, models, comparative study
Procedia PDF Downloads 534739 Vehicle Gearbox Fault Diagnosis Based on Cepstrum Analysis
Authors: Mohamed El Morsy, Gabriela Achtenová
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Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs. This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of cepstrum analysis in detection and diagnosis of the gear condition.Keywords: cepstrum analysis, fault diagnosis, gearbox, vibration signals
Procedia PDF Downloads 371