Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty
Jacobien H. F. Oosterhoff; Anne de Hond; Rinne M Peters; Liza N. van Steenbergen; Juliette C. Sorel; Wierd P Zijlstra; Rudolf W. Poolman; David Ring · 2024 · Clinical Orthopaedics and Related Research
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
BACKGROUND: 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…
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Metadata source: OpenAlex · DOI 10.1097/corr.0000000000003018