Area of research
Artificial Intelligence · Health Information Management
Research interest
Research interests include Machine Learning in Healthcare, Bayesian Modeling and Causal Inference, Electronic Health Records Systems, and Bioinformatics and Genomic Networks.
Ethical and Bias Considerations in Artificial Intelligence/Machine Learning
A framework for human evaluation of large language models in healthcare derived from literature review
MedSyn: Text-Guided Anatomy-Aware Synthesis of High-Fidelity 3-D CT Images
Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography
Characterization of Post–COVID-19 Definitions and Clinical Coding Practices: Longitudinal Study
Potential pitfalls in the use of real-world data for studying long COVID
Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes
Distinguishing Admissions Specifically for COVID-19 From Incidental SARS-CoV-2 Admissions: National Retrospective Electronic Health Record Study
International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality
Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data
Categorizing metadata to help mobilize computable biomedical knowledge
Development of a Coronavirus Disease 2019 (COVID-19) Application Ontology for the Accrual to Clinical Trials (ACT) network
The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment
Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis
Interactive NLP in Clinical Care: Identifying Incidental Findings in Radiology Reports
Accrual to Clinical Trials (ACT): A Clinical and Translational Science Award Consortium Network
Translational bioinformatics in mental health: open access data sources and computational biomarker discovery