Area of research
Artificial Intelligence · Molecular Biology
Research interest
Research interests include Machine Learning in Healthcare, Biomedical Text Mining and Ontologies, Topic Modeling, and Health Literacy and Information Accessibility.
Outcomes of KDIGO-Defined CKD in U.S. Veterans With HFpEF, HFmrEF, and HFrEF
Renin Angiotensin Inhibition and Lower Risk of Kidney Failure in Patients with Heart Failure
Identification and Outcomes of KDIGO-Defined Chronic Kidney Disease in 1.4 Million U.S. Veterans with Heart Failure
ChatGPT-4 extraction of heart failure symptoms and signs from electronic health records
Cardiorespiratory fitness and risk of Alzheimer's disease and related dementias among American veterans
Hybrid Value-Aware Transformer Architecture for Joint Learning from Longitudinal and Non-Longitudinal Clinical Data
Shedding Light on the Black Box: Explaining Deep Neural Network Prediction of Clinical Outcomes
Automated pictographic illustration of discharge instructions with Glyph: impact on patient recall and satisfaction
Identification and Use of Frailty Indicators from Text to Examine Associations with Clinical Outcomes Among Patients with Heart Failure.
PubMed 2016cited by 37position: last
Automated alerts and reminders targeting patients: A review of the literature
Ginkgo and Warfarin Interaction in a Large Veterans Administration Population.
PubMed 2015cited by 46position: last
Regular expression-based learning to extract bodyweight values from clinical notes
Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches
Learning regular expressions for clinical text classification
Predicting sample size required for classification performance
Active learning for clinical text classification: is it better than random sampling?
Limbic system white matter microstructure and long-term treatment outcome in major depressive disorder: A diffusion tensor imaging study using legacy data