Foresight-a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study.

ABSTRACT:

Background

An electronic health record (EHR) holds detailed longitudinal information about a patient's health status and general clinical history, a large portion of which is stored as unstructured, free text. Existing approaches to model a patient's trajectory focus mostly on structured data and a subset of single-domain outcomes. This study aims to evaluate the effectiveness of Foresight, a generative transformer in temporal modelling of patient data, integrating both free text and structured formats, to predict a diverse array of future medical outcomes, such as disorders, substances (eg, to do with medicines, allergies, or poisonings), procedures, and findings (eg, relating to observations, judgements, or assessments).

Methods

Foresight is a novel transformer-based pipel

SUBMITTER: Kraljevic Z 

PROVIDER: S-EPMC11220626 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature