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 5 of 5 for “"Machine Learning for Healthcare"”.
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Machine Learning for Sepsis Prognosis: Prediction Models and Dissecting Electronic Health Records
… extensive research in the area has been performed to facilitate sepsis diagnosis. Sepsis prognosis can support the assessment of the likely progression of the disease and thus inform treatment decisions, but it is much less explored. Here I present two approaches to build sepsis prognosis …
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Evaluating Bias in Machine Learning-Enabled Radiology Image Classification
As machine learning grows more prevalent in the medical field, it is important to ensure that fairness is considered as a central criterion in the evaluation of algorithms and models. Building upon previous work, we study a set of machine learning models used to detect spinal fractures, comparing …
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Machine Learning Approaches for Equitable Healthcare
… about the equity and fairness of the resulting machine learning models. Because the observational data we collect can be noisy, incomplete, and biased, seemingly straight-forward implementation of existing methods for clinical intervention or better understanding human knowledge can lead to …
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Artificial Intelligence for System Medicine: Methods and Applications
… we call system medicine, provides opportunities for clinical and operational systems to improve disease diagnosis, operational efficiency, and, most importantly, clinical understanding. This thesis aims to develop and validate novel methods using artificial intelligence and optimization to …
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Neural Sequence Modeling for Domain-Specific Language Processing: A Systematic Approach
In recent years, deep learning based sequence modeling (neural sequence modeling) techniques have made substantial progress in many tasks, including information retrieval, question answering, information extraction, machine translation, etc. Benefiting from the highly scalable attention-based …