Leveraging large language models to unlock and synthesize the expanding volume of medical research
The overwhelming volume of published research hampers evidence-based medicine. The project team aims to develop MedLitGrasp, an online tool for researchers and clinicians, that uses large language models to automatically synthesize large volumes of biomarker data on multiple sclerosis, stroke, and delirium. This will improve clinical care in Zurich and beyond.
Team
Dr. Benjamin Ineichen, UZH Center for Reprducible Science
Prof. Dr. Beate Sick, ZHAW School of Engineering
Dr. Martin Frey, ZHAW School of Engineering
Practice partner
NEXUS Personalized Health Technologies
Charité Universitätsmedizin Berlin
Running time: 2025-2028