Evaluating the fairness and accuracy of machine learning–based predictions of clinical outcomes after anatomic and reverse total shoulder arthroplasty-Reference-Cited by-同舟云学术

Evaluating the fairness and accuracy of machine learning–based predictions of clinical outcomes after anatomic and reverse total shoulder arthroplasty

Published:2023-09 Issue: Volume: Page:
ISSN:1058-2746
Container-title:Journal of Shoulder and Elbow Surgery
language:en
Short-container-title:Journal of Shoulder and Elbow Surgery

Author:

Allen Christine^ORCID,Kumar Vikas^ORCID,Elwell Josie^ORCID,Overman Steven^ORCID,Schoch Bradley S.^ORCID,Aibinder William^ORCID,Parsons Moby^ORCID,Watling Jonathan,Ko Jiawei Kevin,Gobbato Bruno^ORCID,Throckmorton Thomas^ORCID,Routman Howard^ORCID,Roche Christopher P.^ORCID

Publisher

Elsevier BV

Subject

Orthopedics and Sports Medicine,General Medicine,Surgery

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Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Impact of Deltoid Computer Tomography Image Data on the Accuracy of Machine Learning Predictions of Clinical Outcomes after Anatomic and Reverse Total Shoulder Arthroplasty;Journal of Clinical Medicine;2024-02-23

2. Initial clinical experience with a predictive clinical decision support tool for anatomic and reverse total shoulder arthroplasty;European Journal of Orthopaedic Surgery & Traumatology;2023-12-14