Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review.

ABSTRACT: Background and purpose - External validation of machine learning (ML) prediction models is an essential step before clinical application. We assessed the proportion, performance, and transparent reporting of externally validated ML prediction models in orthopedic surgery, using the Transparent Reporting for Individual Prognosis or Diagnosis (TRIPOD) guidelines.Material and methods - We performed a systematic search using synonyms for every orthopedic specialty, ML, and external validation. The proportion was determined by using 59 ML prediction models with only internal validation in orthopedic surgical outcome published up until June 18, 2020, previously identified by our group. Model performance was evaluated using discrimination, calibration, and decision-curve analysis. The TRIPOD guid

SUBMITTER: Groot OQ 

PROVIDER: S-EPMC8436968 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature