Leveraging Large Language Models to Derive Multiple Sclerosis Progression Assessments from Clinical Notes: A Feasibility Study
Year: 2025
Type: conference-paper
Abstract: Ascertainment of multiple sclerosis (MS) progression is important for informing clinical care decisions and supporting biomedical research. However, the details to infer a patient's MS progression status are locked within clinical notes. In this feasibility study, we assessed the feasibility of developing and validating a large language model (LLM)-based EDSS and FS classifier for ascertaining MS progression from clinical notes.
Authors: Sy Hwang, Sunil Thomas, Heather Williams, Tom Hutchinson, Emily Schriver, Ashley Batugo, Amit Bar-Or, Vishakha Sharma, Frederik Buijs, Christopher Perrone, Danielle Mowery
Institutions: University of Pennsylvania, Roche (Switzerland)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4417312675