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We are a collaborative research group in Medicine and Biomedical Engineering at Johns Hopkins University.
Learn MoreOur research draws from biomedical informatics and the related field of biomedical data science to address challenges to translating discoveries into practice.
Learn MoreWe pursue projects that address the challenge of how to incorporate technology and digital approaches into research and clinical practices.
Learn MoreWe are looking for passionate new PhD students, Master and Bachelor students to join the team.
Learn MoreNidhi Soley had a podium presentation at the 2024 BMES Annual Meeting in Baltimore, MD.
October 7, 2024Our article titled Patterns of healthcare utilization according to health equity determinants during the first year of the pandemic at Johns Hopkins Medicine was published in JAMIA Open.
September 30, 2024Our article titled Usability, Engagement, and Report Usefulness of Chatbot-Based Family Health History Data Collection - Mixed Methods Analysis was published in Journal of Medical Internet Research.
September 20, 2024Welcome to Tamisha Segbefia joining the lab as a Research Program Assistant.
July 9, 2024Michelle Nguyen, Ilia Rattsev, and April Yan presented at the 22nd International Conference on Artificial Intelligence in Medicine (AIME 2024) in Salt Lake City, Utah.
June 1, 2024Our article titled Predicting Postoperative Pain and Opioid Use with Machine Learning Applied to Longitudinal Electronic Health Record and Wearable Data was published in Applied Clinical Informatics.
May 28, 2024Tamisha Dzifa Segbefia completed her MS in Biomedical Engineering (BME) and her thesis titled "Characterizing Polygenic Risk Scores Among A Cohort of Breast Cancer Cases and Controls in the All of Us Research Program." She also contributed to work with other lab members designing software intended for genomic medicine service leaders presented at IEEE ICHI 2023. Sukrit Treewaree completed his MS in BME. He has contributed to lab projects underway using LLMs to generate synthetic drug-related patient portal messages and using observational clinical data to detect drug switches.
Febuary 9, 2024April Yan, Iyinoluwa Tugbobo, Ilya Rattsev, Michelle Nguyen, Shanshan Song, and Tamisha Segbefia presented at the 2024 Department of Medicine & Whiting School of Engineering Research Retreat Poster Session on February 9, 2024.
January 30, 2024Our article titled Incorporation of emergent symptoms and genetic covariates improves prediction of aromatase inhibitor therapy discontinuation was published in JAMIA Open (online ahead of print).