Machine learning-based prediction models for pressure injury: A systematic review and meta-analysis.

ABSTRACT: Despite the fact that machine learning (ML) algorithms to construct predictive models for pressure injury development are widely reported, the performance of the model remains unknown. The goal of the review was to systematically appraise the performance of ML models in predicting pressure injury. PubMed, Embase, Cochrane Library, Web of Science, CINAHL, Grey literature and other databases were systematically searched. Original journal papers were included which met the inclusion criteria. The methodological quality was assessed independently by two reviewers using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Meta-analysis was performed with Metadisc software, with the area under the receiver operating characteristic curve, sensitivity and specificity as effect measures. Ch

SUBMITTER: Pei J 

PROVIDER: S-EPMC10681397 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature