Skip to main content

Dissertations and Theses (Open Access)

Open Access full-text dissertations from McWilliams School of Biomedical Informatics at UTHealth Houston, formerly UTHealth Houston School of Biomedical Informatics (SBMI). 2003 - current.

A few older copies (2003-2008) are also available in print at The TMC Library. They're available via OneSearch under the subject heading: "Dissertations, Academic--University of Texas Health Science Center at Houston, School of Health Information Sciences" for a full list, or search for known individual dissertations using the main search box or the DigitalCommons@TMC search box in the white banner above.

Dissertations from 2026 2026

Teaching Large Language Models to Understand Biology: Evidence-Grounded Agentic Systems for Brain Cell Type Annotation, Rongbin Li

A Computational Framework for Quantifying Dysregulation and Mapping Pathways using Transcriptomic and Molecular Data and its Application in O-GlcNAcylation, Rastko Stojsin

A Patient-Centric Chatbot for Improving Clinical Trial Accessibility, Yumeng Yang

Graph and Language Models for Biomedical Inference Across Networks and Text, Evan Yu

Dissertations from 2025 2025

Standardizing Social Determinants of Health Factors from Heterogeneous Sources to Improve Data FAIRness, Yifang Dang

A Culturally-Tailored Framework for Improving Patient Activation within a Digital Solution: Supporting Black Pregnant Women with Hypertensive Disorders, Morgan Foreman

Computational Methods for Enhancing the Quality and Interoperability of Biomedical Terminologies, Xubing Hao

Leveraging and Advancing the Foundation Models for Clinical Trajectory Analysis Based on Electronic Health Record Data, Jianping He

Harnessing Knowledge and Data for Clinical Information Extraction in the Era of Large Language Models, Yan Hu

Advancing Genetic Association Discovery in Brain MRI using Unsupervised and Self-supervised Deep Learning: Exploring Learning Dynamics, Region-Specific Features, and Spatially Resolved Representations, Sheikh Muhammad Saiful Islam

Deep Learning Frameworks for Disease Diagnosis and Overall Survival Prediction using Imaging, Genomic and Clinical Data, Tanjida Kabir

Leveraging Observational and RCT Data for Understanding Interventions’ efficacy: Applications in Progressive and Acute Neurological Diseases, Yaobin Ling

Accelerating Drug Repurposing and Target Discovery using Deep Learning, Kohong Lin

Deciphering Medical Imaging from Genetic Data: Integrative Modelling Across Genetics and Imaging Modalities, Wentao Li

MINDFUL: Machine Intelligence Towards Neuropsychiatric Data For Unified Learning, Zehan Li

Precision Drug Dosing and Disease Risk Prediction: Advanced Deep Learning Artificial Intelligence Approaches for Precision Medicine Using Structured Electronic Health Records Data, Bingyu Mao

Deep Learning Frameworks for Disease Detection and Outcome Prediction using Sequential Biomedical Data, Xiaotian Ma

Establishing a Translational Research Framework for Optimizing Clinical Workflows and Care Pathways across the Continuum of Stroke Care: Evaluation of Time Series Derived Patterns in Adverse Health Trajectories among Acute Ischemic Stroke Survivors using Clinical and Medical Claims Linked Data, Alan Pan

Computer-Aided Integrated Rehabilitation for Post-Stroke Patients Using Deep Learning Techniques, Kaichen Tang

From Latent Patterns to Interpretable Subtypes: Machine Learning Driven Subtyping in Alzheimer’s Clinical Trials, Dulin Wang

Dissertations from 2024 2024

Radiation-Induced Lymphopenia: Understanding, Predictive Modelling and Developing Photon and Proton-Based Mitigation Strategies, Yan Chu

Cardiovascular Biomarkers using Deep Learning and Retinal Imaging for the Assessment of Systemic Disease, Ivan Coronado

Multi-omic single-cell integration for understanding T cell responses in Acute Myeloid Leukemia, Poonam Desai

Designing Recommendation Systems for Identification and Reduction of Unnecessary Blood Tests, Tongtong Huang

Comprehensive Analysis of Adverse Events Following COVID-19 Vaccination: Insights from Diverse Data Sources, Yiming Li