Local large language models for privacy-preserving accelerated review of historic echocardiogram reports.

ABSTRACT:

Objectives

The study developed framework that leverages an open-source Large Language Model (LLM) to enable clinicians to ask plain-language questions about a patient's entire echocardiogram report history. This approach is intended to streamline the extraction of clinical insights from multiple echocardiogram reports, particularly in patients with complex cardiac diseases, thereby enhancing both patient care and research efficiency.

Materials and methods

Data from over 10 years were collected, comprising echocardiogram reports from patients with more than 10 echocardiograms on file at the Mount Sinai Health System. These reports were converted into a single document per patient for analysis, broken down into snippets and relevant snippets were retrieved using text similarit

SUBMITTER: Vaid A 

PROVIDER: S-EPMC11339495 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature