Reply to the Letter to the Editor: 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

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Reply to the Letter to the Editor: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?

Published:2020-04-07 Issue:6 Volume:478 Page:1378-1379
ISSN:0009-921X
Container-title:Clinical Orthopaedics & Related Research
language:en
Short-container-title:Clin Orthop Relat Res

Author:

Ghomrawi Hassan M. K.,Mancuso Carol A.,Della Valle Alejandro Gonzalez,Alexiades Michael,Cornell Charles,Sculco Thomas,Bostrom Mathias,Mayman David,Marx Robert G.,Westrich Geoffrey,Mushlin Alvin I.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Orthopedics and Sports Medicine,General Medicine,Surgery

Reference6 articles.

1. Patient satisfaction after total knee arthroplasty: Who is satisfied and who is not?;Bourne;Clin Orthop Relat Res,2010

2. Can machine learning algorithms predict which patients will achieve minimally clinically important differences from total joint arthroplasty?;Fontana;Clin Orthop Relat Res,2019

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

4. Measures of the appropriateness of elective orthopaedic joint and spine procedures;Katz;J Bone Joint Surg Am,2017

5. Appropriateness criteria for total knee arthroplasty: Additional comments and considerations;Riddle;J Bone Joint Surg Am,2018

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