Call for papers - The role of large language models in revolutionizing digital health

Abeed Sarker, PhD, Emory University, USA

Dr Sarker (he/him) is an Associate Professor and the Vice Chair for Research at the Department of Biomedical Informatics, School of Medicine, Emory University. He has over a decade of experience in leading large projects focusing on the application of NLP for health-related tasks, particularly those involving vulnerable populations such as people with substance use disorders, victims of intimate partner violence, and people at risk of self-harm and suicide. His research is primarily funded by the National Institutes of Health (NIH) and Centers for Disease Control and Prevention (CDC). He also co-leads a NIH training (T32) training program focusing at the intersection of  NLP, machine learning and public health. Dr Sarker's research has been covered by various national and international media outlets such as the Wall Street Journal, Forbes, and Scripps National News.

Lina F. Soualmia, PhD, University of Rouen Normandie, France

Dr Lina F. Soualmia is a Professor of computer science at Normandie Université, Univ. Rouen, France. She is IMIA VP for services in charge of the Yearbook of Medical Informatics. Her research interests include clinical language processing, data management and integration, knowledge graphs, and information extraction from texts. In her recent researches she developed new predicting models founded on neuro-symbolic approaches mixing deep learning and reasoning on graphs. She is a member of the Editorial Board of the BMC Digital Health journal and BMC Medical Informatics and Decision Making.

Honghan Wu, PhD, University of Glasgow, UK

Honghan Wu is a Professor in Health Informatics and Data Science, University of Glasgow, United Kingdom, and a former Fellow of The Alan Turing Institute. He is a specialist in health informatics, particularly interested in using text analysis and knowledge graphs to analyze electronic health records (EHRs). His goal is to develop methods to extract meaningful information from complex medical data to support better patient care, clinical trials, and healthcare research. Prof Wu leads a health informatics group and collaborates with the National Health Service (NHS) to implement these techniques for practical applications. His research focuses on using AI to improve how we manage and treat various health conditions, including mental health, diabetes, and cardiovascular disease.