Machine learning classifiers do not improve prediction of hospitalization > 2 days after fast-track hip and knee arthroplasty compared with a classical statistical risk model

Machine learning classifiers do not improve prediction of hospitalization > 2 days after fast-track hip and knee arthroplasty compared with a classical statistical risk model

Background and purpose — Prediction of postoperative outcomes and length of hospital stay (LOS) of patients is vital for allocation of healthcare resources. We investigated the performance of prediction models based on machinelearning algorithms compared with a previous risk stratification model usi...

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Bibliographic Details
Main Authors: Katrin B Johannesdottir, Henrik Kehlet, Pelle B Petersen, Eske K Aasvang, Helge B D Sørensen, Christoffer C Jørgensen
Format: Article
Language:English
Published: Medical Journals Sweden 2022-01-01
Series:Acta Orthopaedica
Subjects:
Arthroplasty
Hip
Knee
Length of hospital stay
Outcome
Prediction
Online Access:https://actaorthop.org/actao/article/view/843

Internet

https://actaorthop.org/actao/article/view/843

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