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 8 of 8 for “"Depression detection"”.
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Developing Deep Learning Models for Depression Detection in Texts
Depression is a major mental health disorder affecting a significant portion of the world population. Methods mostly being employed for depression detection are clinical interviews and questionnaire surveys where psychiatric assessment tables are used to establish mental disorder prognosis. …
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Generalizable Depression Detection and Severity Prediction Using Articulatory Representations of Speech
… in speech characteristics that occur due to depression, a lot of vocal biomarkers are being developed to detect depression. However, the study into changes in articulatory coordination associated with depression is under-explored. Speech articulation is a complex activity that requires finely …
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Comparison of Natural Language Processing Models for Depression Detection in Chatbot Dialogues
Depression is an important challenge in the world today and a large source of disability. In the US, a recent study showed that approximately 36 million adults had at least one major depressive episode, including some with severe impairment [1]. However, approximately two-thirds of all depression …
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Expresso-AI : a framework for explainable video based deep learning models through gestures and expressions
… Facial Videos and applying it to Automatic Depression Detection. We also developed a video based models We have developed a framework to analyze the decisions of Deep Neural Networks trained on facial videos. We test this framework on Automatic Depression Detection. We first train Deep …
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Early Detection of Depression
Depression is a mental disorder that affects more than 300 million people worldwide. An individual suffering from depression functions poorly in life, is prone to other diseases and in the worst-case, depression leads to suicide. There are many impediments that prevent expert care from reaching …
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Speech-Based Emotion Modelling and Mental Disorder Detection
… as speech quality assessment and toxic speech detection. A general framework for human annotator simulation is introduced, which accounts for the variability in human judgements. The framework meta-learns a conditional flow model, which demonstrates superior capability and efficiency in …
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Beyond clinical thresholds: the continuum of depressive symptoms and their influence on diabetes outcomes
… rise to 783 million by 2045. The prevalence of depression in diabetes is doubled compared to people without diabetes. This comorbidity has been associated with greater risk of mortality, cognitive decline, and diabetes complications. The aim of this thesis was to advance knowledge on the role of …
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Toward Robust and Generalizable Spatiotemporal Modeling for Tasks beyond Forecasting and Classification
… forecasting and classification: anomaly detection, domain adaptation, and causal discovery. It systematically examines these issues across three cross-disciplinary application domains and proposes targeted, scenario-specific solutions: textbf{(1) Anomaly Detection:} We develop …