Prediction models using artificial intelligence and longitudinal data from electronic health records: a systematic methodological review.

ABSTRACT:

Objective

To describe and appraise the use of artificial intelligence (AI) techniques that can cope with longitudinal data from electronic health records (EHRs) to predict health-related outcomes.

Methods

This review included studies in any language that: EHR was at least one of the data sources, collected longitudinal data, used an AI technique capable of handling longitudinal data, and predicted any health-related outcomes. We searched MEDLINE, Scopus, Web of Science, and IEEE Xplorer from inception to January 3, 2022. Information on the dataset, prediction task, data preprocessing, feature selection, method, validation, performance, and implementation was extracted and summarized using descriptive statistics. Risk of bias and completeness of reporting were assessed using

SUBMITTER: Carrasco-Ribelles LA 

PROVIDER: S-EPMC10654870 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature