Ph.D. Gallery

Acoustic and Linguistic Analysis in Neurological and Psychiatric Disorders This thesis investigates the application of speech and language analysis for clinical evaluation and monitoring of neurological and psychiatric disorders, specifically Major Depression Disorder (MDD), Alzheimer's Disease ...

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Phonetic Transfer Learning from Healthy References for the Analysis of Pathological Speech Automatic speech recognition (ASR) experienced a major leap forward through many advances in deep machine learning over the past decade. In each new iteration of neural ASR architecture, the increase in pe...

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Hybrid Machine Learning Approaches for Image Reconstruction and Processing in Low-Dose Computed Tomography Diagnostic decisions in clinical workflows often hinge on the interpretation of medical images. The inherent quality of these images plays a critical role in discerning relevant anatomical ...

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Deep Learning-based Grading of Coronary Artery Disease from Coronary CT Angiography Scans One of the deadliest disease types in modern societies is coronary artery disease (CAD). It is often related to coronary artery plaques aggregating within the vessel wall obstructing the lumen causing a ste...

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Deep Learning and Computational Modeling of Physiology Deep Learning (DL) and computational modeling (CM) could revolutionize the healthcare system by personalizing therapies to patients and enabling precision medicine (PM). While DL can automatically extract decision rules from large amounts of...

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Data-Driven Derivation of Rheumatological Disease Characteristics from Medical Images Rheumatologists have various tools at hand that allow characterizing the diseases of their patients. A multitude of those tools requires human annotation, which in some cases is time-intensive and error-prone. ...

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Deep Learning and Image Processing for Stroke Diagnosis with Computed Tomography Angiography Computed Tomography (CT) is an effective tool, especially in acute situations, which contributes significantly to diagnosing a wide variety of clinical pictures. This includes, with a high prevalence, is...

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Deep Learning Applied to Animal Linguistics Even nowadays, people have only a very limited understanding about animal communication. Scientists are still far from identifying statistically relevant, animal-specific, and recurring linguistic paradigms. However, combined with the associated situat...

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