Enhancing early detection of cognitive decline in the elderly: a comparative study utilizing large language models in clinical notes.

ABSTRACT:

Background

Large language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing their error profiles with traditional models. The insights gained will inform strategies for performance enhancement.

Methods

This study, conducted at Mass General Brigham in Boston, MA, analysed clinical notes from the four years prior to a 2019 diagnosis of mild cognitive impairment in patients aged 50 and older. We developed prompts for two LLMs, Llama 2 and GPT-4, on Health Insurance Portability and Accountability Act (HIPAA)-compl

SUBMITTER: Du X 

PROVIDER: S-EPMC11663780 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature