Detecting New Lesions Using a Large Language Model: Applications in Real-World Multiple Sclerosis Datasets.

ABSTRACT:

Objective

Neuroimaging is routinely utilized to identify new inflammatory activity in multiple sclerosis (MS). A large language model to classify narrative magnetic resonance imaging reports in the electronic health record (EHR) as discrete data could provide significant benefits for MS research. The objectives of the current study were to develop such a prompt and to illustrate its research applications through a common clinical scenario: monitoring response to B-cell depleting therapy (BCDT).

Methods

An institutional ecosystem that securely connects healthcare data with ChatGPT4 was applied to clinical MS magnetic resonance imaging reports in a single institutional EHR (2000-2022). A prompt (msLesionprompt) was developed and iteratively refined to classify the presence or

SUBMITTER: Poole S 

PROVIDER: S-EPMC12278027 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature