Open Access. Powered by Scholars. Published by Universities.®

Biomedical Informatics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 2 of 2

Full-Text Articles in Biomedical Informatics

Bridging Data Gaps In Retinal Imaging: From Structural Domain Adaptation To Topology-Aware Synthesis, Gözde Merve Demirci Sep 2026

Bridging Data Gaps In Retinal Imaging: From Structural Domain Adaptation To Topology-Aware Synthesis, Gözde Merve Demirci

Dissertations, Theses, and Capstone Projects

Comprehensive visualization of the retina is essential for diagnosing and monitoring blinding diseases such as Diabetic Retinopathy and Retinopathy of Prematurity (ROP), where pathological changes often extend beyond a single field of view. Despite significant advances in automated retinal image analysis, clinical deployment remains limited by two fundamental data gaps: a structural learning gap, arising from scarce expert annotations and poor generalization across imaging domains, and a spatial coverage gap, caused by the difficulty of acquiring multi-view retinal images in fragile populations. Although these challenges are often addressed independently, this dissertation argues that they are tightly coupled: accurate, …


Ai-Powered Multi-Omics Integration For Predictive Modeling Of Genotype-Environment-Phenotype Relationships, You Wu Sep 2025

Ai-Powered Multi-Omics Integration For Predictive Modeling Of Genotype-Environment-Phenotype Relationships, You Wu

Dissertations, Theses, and Capstone Projects

This dissertation presents a series of machine learning frameworks for modeling genotype–environment–phenotype relationships through integrative predictive modeling of multi-omics data. The work addresses three major axes of biological complexity: modeling biological information transmission cross-levels from genes to proteins to phenotypes, predicting molecular features cross-scale from cells to tissues to organisms, and translating phenotypes cross-species from model systems to humans. Each proposed method also tackles key machine learning (ML) challenges in the biomedical domain, including data scarcity, domain shift, out-of-distribution (OOD) generalization, and hierarchical modeling. Specifically, this dissertation introduces five novel deep learning algorithms: MultiDCP predicts drug-induced transcriptomic and viability responses …