Dataset Information
Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.
Ontology highlight
ABSTRACT:
SUBMITTER: Oosterhoff JHF
PROVIDER: S-EPMC11272341 | biostudies-literature | 2024 Aug
REPOSITORIES: biostudies-literature
Publications
Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.
Clinical orthopaedics and related research 20240312 8
<h4>Background</h4>Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling approaches such as traditional survivorship estimators (such as Kaplan-Meier) or competing risk estimators. Recent advances in machine learning survival analysis might improve decision support tools in this setting. Therefore, this study aimed ...[more]