Predicting ACL Reconstruction Failure with Machine Learning: Development of Machine Learning Prediction Models.

ABSTRACT:

Background

Anterior cruciate ligament reconstruction (ACLR) is the predominant and widely accepted treatment modality for ACL injury. However, recurrence of ACL rupture or failure of the reconstruction remains a significant challenge. Despite several studies in the literature that have developed prediction models to address this issue by identifying prognostic factors for treatment outcomes using classical statistical methods, the predictive efficacy of these models is frequently suboptimal.

Purpose

To (1) evaluate the predictive performance of different machine learning algorithms for the occurrence of failure in ACLR and (2) identify the most relevant predictors associated with this outcome.

Study design

Cohort study; Level of evidence, 3.

Methods

A total of

SUBMITTER: Alaiti RK 

PROVIDER: S-EPMC11938500 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature