Wide range of applications for machine-learning prediction models in orthopedic surgical outcome: a systematic review.

ABSTRACT: Background and purpose - Advancements in software and hardware have enabled the rise of clinical prediction models based on machine learning (ML) in orthopedic surgery. Given their growing popularity and their likely implementation in clinical practice we evaluated which outcomes these new models have focused on and what methodologies are being employed.Material and methods - We performed a systematic search in PubMed, Embase, and Cochrane Library for studies published up to June 18, 2020. Studies reporting on non-ML prediction models or non-orthopedic outcomes were excluded. After screening 7,138 studies, 59 studies reporting on 77 prediction models were included. We extracted data regarding outcome, study design, and reported performance metrics.Results - Of the 77 identified ML predicti

SUBMITTER: Ogink PT 

PROVIDER: S-EPMC8519550 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature