Editor’s Spotlight/Take 5: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?-Reference-Cited by-同舟云学术

Editor’s Spotlight/Take 5: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?

Published:2019-05-15 Issue:6 Volume:477 Page:1262-1266
ISSN:0009-921X
Container-title:Clinical Orthopaedics & Related Research
language:en
Short-container-title:Clin Orthop Relat Res

Author:

Leopold Seth S.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Orthopedics and Sports Medicine,General Medicine,Surgery

Reference12 articles.

1. Do surgeon expectations predict clinically important improvements in WOMAC scores after THA and TKA?;Ghomrawi;Clin Orthop Relat Res,2017

2. Can machine learning methods produce accurate and easy-to-use prediction models of 30-day complications and mortality after knee or hip arthroplasty?;Harris;Clin Orthop Relat Res,2019

3. Breast Cancer Surveillance Consortium. Diagnostic accuracy of digital screening mammography with and without computer-aided detection;Lehman;JAMA Intern Med,2015

4. Editorial: The minimum clinically important difference—The least we can do;Leopold;Clin Orthop Relat Res,2017

5. Editor’s Spotlight/Take 5: Is changing hospitals for revision total joint arthroplasty associated with more complications?;Leopold;Clin Orthop Relat Res,2014

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