Department of Medical Informatics and Clinical Epidemiology

Developing software to extract patient characteristics data from randomized controlled trials in .pdf format. The software extracts the data via LLM and returns a .csv do [...]

Many social determinants of health (SDOH) impact one’s ability to engage in healthcare, including access to and usability of health information technology. A key goal of [...]

This work is an effort to characterize the nature of text-based communication behaviors between healthcare providers at a tertiary-care freestanding children’s hospital, [...]

Patient data entry burden remains a challenge. This study evaluated vector embedding search and large language models (LLMs) for automated schema matching between medical [...]

Here we evaluated the accuracy of several freely available software packages to correct for variable gene copy numbers in microbiome profiling using the 16S rRNA gene. We [...]

The work presented in this dissertation focuses on the development of robust deep learning models to predict in-vitro cancer drug responses, with utility in precision onc [...]

This novel computational framework for the analysis of single-cell gene expression data from human tumor samples enables the identification of molecular activity associat [...]

Anomia is the inability to access and retrieve the intended words during language production, and is a cardinal feature of the acquired neurogenic language disorder known [...]

The significant inter- and intra-tumor heterogeneity observed in breast cancer patients presents an ongoing challenge that impedes accurate disease characterization and c [...]

Accurate model representation is critical for conveying assumptions and guiding data analysis, especially when using observational data. This qualitative study employed a [...]