Factors underpinning the performance of implemented artificial intelligence-based patient deterioration prediction systems: reasons for selection and implications for hospitals and researchers.

ABSTRACT:

Objective

The degree to which deployed artificial intelligence-based deterioration prediction algorithms (AI-DPA) differ in their development, the reasons for these differences, and how this may impact their performance remains unclear. Our primary objective was to identify design factors and associated decisions related to the development of AI-DPA and highlight deficits that require further research.

Materials and methods

Based on a systematic review of 14 deployed AI-DPA and an updated systematic search, we identified studies of 12 eligible AI-DPA from which data were extracted independently by 2 investigators on all design factors, decisions, and justifications pertaining to 6 machine learning development stages: (1) model requirements, (2) data collection, (3) data clea

SUBMITTER: van der Vegt AH 

PROVIDER: S-EPMC11833469 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature