Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 26 for “"disease classification"”.
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Capnographic analysis for disease classification
… physiological waveform features and performing classification by discriminant analysis with voting. Our classification methods are tested in distinguishing between records from subjects with normal lung function and patients with cardiorespiratory disease. In a second step, we discriminate …
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Arrhythmia heart disease classification using deep learning
… cause about half of deaths due to cardiovascular disease and about 15% of all deaths globally. About 80% of sudden cardiac death is the result of ventricular arrhythmias. Arrhythmias may occur at any age but are more common among older people. Arrhythmias are caused by problems with the electrical …
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Biologically-Interpretable Disease Classification Based on Gene Expression Data
Classification of tissues and diseases based on gene expression data is a powerful application of DNA microarrays. Many popular classifiers like support vector machines, nearest-neighbour methods, and boosting have been applied successfully to this problem. However, it is difficult to determine …
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The relationship between HIV disease classification and depression and suicidal intent
… was to investigate the relationship between HIV disease classification, depression and suicidal intent. A convenience sample of eighty HIV infected persons was obtained from The Bering Care Center in Houston, Texas. The Beck Depression Inventory (BDI), the Hopelessness Scale (HS), and a …
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Optimal Analytical Methods for High Accuracy Cardiac Disease Classification and Treatment Based on ECG Data
… Component Analysis (PCA) application in classification problem was studied. PCA is a commonly used technique to reduce dimensions of the data through analyzing correlation structure of the original variables. This reduction is achieved by considering only the first few principal …
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Towards Data-Driven Cognitive Disease Classification using Machine Learning and the Digital Symbol Digit Test
… is no cure for Alzheimer’s and other cognitive diseases; however, there are treatments that help slow disease progression. Early detection of neurological dysfunction is often caught through screening tests like the Symbol Digit Test. Researchers at MIT and Lahey have been administering the …
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Diagnosis for Patient and GP: Dialogue-based Self-Diagnosis with Disease-Symptoms Graph and Referral Letter Classification
… lim- itations in user interface and scope of diseases covered. In re- sponse, this study devised a dialogue-based self-diagnosis system. By harnessing data from the National Health Service (NHS) web- site, this thesis established a method to identify symptoms and generated a mapping of …
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Development of a Bagging-based Ensemble Model for ECG Classification
… of machine learning models in cardiovascular disease classification and recognition, is rapidly growing. CNN, LSTM, and Transformer models have demonstrated in various studies that, when implemented with robust architectures and supported by ample datasets, they can achieve highly accurate …
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Non-parametric algorithms for evaluating gene expression in cancer using DNA microarray technology
… to find gene expression markers that cluster diseased and normal tissues, genes affected by treatments, and gene network interactions. All methods of microarray data analysis can be summarized as a study of differential gene expression. This study addresses three questions, 1) the roles of …
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The Rude Unhinging: A Study of Shock
… significant change. From a practice of nosology, disease classification, and a focus on the subjective and the symptom emerged an epistemology that looked for objective clinical signs that denoted the presence in the body of disease-defining pathologic lesions. Yet this physical, tangible identity …
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"Can I get a second opinion?" How user characteristics impact trust in automation in a medical screening task
… medical field, advances in automation allow for disease classification, diagnosis, and even treatment recommendations. Technological advances have improved diagnoses by automated devices such that many cases can be more accurately diagnosed by a computer program than by a medical doctor. The …
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A comparative evaluation of surrogate measures of adiposity as indictors of cardiometabolic disease
… clinical practice, and whether methods used for disease classification and anthropometric measurement procedure are important for diagnosing cardiometabolic risk and type 2 diabetes; (2) to compare adiposity variable relationships with a range of cardiometabolic disease features, biomarkers of …
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Factors associated with outcomes of patients placed on tuberculosis treatment in the western geographic service area of Cape Town
… association between treatment outcome and sex, disease classification, treatment regimen, HIV status and patient category. Conclusion A high proportion of incident TB cases had previously been treated for TB. Overall treatment outcomes were poor. Unfavourable treatment outcomes were more common …
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An exploration of the cultural context and consequences of perceptions of illness and health-seeking behaviour of the Baloch
… regarding the origin and cause of illness and disease as revealed in their system of disease-classification and their etiological categories. It was also to describe the context in which Baloch access the traditional health care system as well as conventional health care. Participant …
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Enhancing Microbiome Host Disease Prediction with Variational Autoencoders
… implicate further potential for progress in disease diagnosis and treatment in humans. The ability to classify a human microbiome profile into a disease category, and additionally identify the differentiating factors within the profile between diseased and healthy individuals are valuable …
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Identification Of Neuroblastoma And Its Prognostic Markers Using Raman Spectroscopy
… of a sample. It has recently been applied to disease classification, specifically in adult cancers.</p> <p><strong>Methods</strong>: To identify neuroblastoma from adrenal gland, peripheral nervous system tumors, and small round blue cell tumors, and to identify tumor histology, fresh and …
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Biomarker Discovery in Autoimmune Diseases: A Proteomics Approach
… machinery of cells and are prime candidates for disease marker discovery. Mass spectrometry-based proteomics biomarker discovery holds the ability to interrogate a constellation of proteins simultaneously in a high-throughput manner to uncover a panel of markers that are specific to the presence …
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Deep Learning for Early Detection, Identification, and Spatiotemporal Monitoring of Plant Diseases Using Multispectral Aerial Imagery
… crops is hampered by the proliferation of crop diseases which cause huge harvest losses. Current crop-health monitoring programs involve the deployment of scouts and experts to detect and identify crop diseases through visual observation. These monitoring schemes are expensive and too slow to …
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Predicting the Effectiveness of Medical Interventions
… treatments is crucial to mitigating death and disease and improving individual and population health, yet generating such predictions is fraught with difficulties. Each chapter deals with a unique challenge to predictions of medical effectiveness. In Chapter 1, I describe and analyze the …
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