Large Language Model-Based Critical Care Big Data Deployment and Extraction: Descriptive Analysis.

ABSTRACT:

Background

Publicly accessible critical care-related databases contain enormous clinical data, but their utilization often requires advanced programming skills. The growing complexity of large databases and unstructured data presents challenges for clinicians who need programming or data analysis expertise to utilize these systems directly.

Objective

This study aims to simplify critical care-related database deployment and extraction via large language models.

Methods

The development of this platform was a 2-step process. First, we enabled automated database deployment using Docker container technology, with incorporated web-based analytics interfaces Metabase and Superset. Second, we developed the intensive care unit-generative pretrained transformer (ICU-GPT), a lar

SUBMITTER: Yang Z 

PROVIDER: S-EPMC11922493 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature