Clinical NLP chapter published in the Springer Handbook of Data Engineering
Kevin Lybarger, Hadeel Elyazori, and Mohammad Sabik Irbaz wrote “Natural Language Processing of Clinical Data” with Özlem Uzuner, Giridhar Kaushik Ramachandran, and A. H. M. Rezaul Karim for the Springer Handbook of Data Engineering, edited by Fatos Xhafa. The chapter, a primer on clinical NLP, covers clinical documents and annotated datasets, data quality and privacy challenges, and methods from rule-based systems to large language models, and explains how to frame clinical problems as NLP tasks. Read the chapter (image courtesy of Springer).
Tanvir's patient simulation paper published in JMIR AI
Md Tanvir Rouf Shawon's paper with Mohammad Sabik Irbaz, Hadeel Elyazori, and collaborators is now published in JMIR AI. It describes a framework for testing conversational health AI before deployment by simulating patients who differ in medical history, health literacy, and conversational behavior. Applied to a decision aid for antidepressant selection, the simulations showed the aid ranked the correct clinical concept first 82% of the time for patients with proficient health literacy and 48% of the time for patients with limited health literacy. Read the paper (figure from the paper).
Hadeel to join healthcare access panel at Mason
Hadeel Elyazori will join a panel on healthcare access across diverse populations, alongside Hoangmai Pham (Institute for Exceptional Care), Lacretia Smith, and Amanda Sanchez, moderated by Gilbert Gimm. Hosted by George Mason's Office of Community Engagement and Civic Learning (CECiL) and the Center for MedTech Innovation, the panel and roundtable run 11:30am–2:00pm on October 15, 2026, at the Johnson Center's George's Café. Register.
Tanvir's paper accepted in JMIR AI
Congratulations to Md Tanvir Rouf Shawon on the acceptance of his paper on Patient Simulation in JMIR AI.
Hadeel passed her comprehensive exam
Congratulations to Hadeel Elyazori on passing her comprehensive exam.
PCORI award to improve depression treatment using AI
Dr. Alemi and Dr. Lybarger received a $1,049,998 award from the Patient-Centered Outcomes Research Institute (PCORI) for their 3-year project, Evaluating Conversational Artificial Intelligence for Depression Management. The project explores applications of large language models to improve antidepressant recommendations and patient outcomes. Details on the PCORI website and the GMU website.
NIH grant to pilot AI chatbot for African Americans with depression
George Mason University's College of Public Health received a $70,906 NIH AIM-AHEAD grant to develop and test an AI chatbot that recommends antidepressants for African Americans with depression, aiming to address gaps in personalized treatment. Details in the George Mason announcement.
n2c2 SDOH extraction challenge paper published in JAMIA
The paper describing the National NLP Clinical Challenges (n2c2) extraction task, Track 2: Extracting Social Determinants of Health, was published in JAMIA. Challenge participants used a wide range of innovative techniques.
JAMIA focus issue on extracting SDOH
The Journal of the American Medical Informatics Association published a call for papers for a focus issue, Social Determinants of Health (SDOH) Extraction through Natural Language Processing, with submissions due in early December.
AMIA work exploring digital scribes and transcribed patient visits was featured in an article by Fierce Healthcare.
Talk at the UW Center for Studies in Demography & Ecology
Kevin Lybarger presented his social determinants of health research to the UW Center for Studies in Demography & Ecology on November 5, 2021.
AMIA presentations
At the AMIA Virtual Day on October 26, 2021, Kevin Lybarger presented a paper on automatic identification of acute respiratory distress syndrome (ARDS) in chest radiograph reports (paper) and a poster on applying information extraction models to transcribed patient visits.
Lybarger 
