Development of Machine Learning Algorithms to Predict Clinically Meaningful Improvement for the Patient-Reported Health State After Total Hip Arthroplasty-Reference-Cited by-同舟云学术

Development of Machine Learning Algorithms to Predict Clinically Meaningful Improvement for the Patient-Reported Health State After Total Hip Arthroplasty

Published:2020-08 Issue:8 Volume:35 Page:2119-2123
ISSN:0883-5403
Container-title:The Journal of Arthroplasty
language:en
Short-container-title:The Journal of Arthroplasty

Author:

Kunze Kyle N.,Karhade Aditya V.,Sadauskas Alex J.,Schwab Joseph H.,Levine Brett R.

Publisher

Elsevier BV

Subject

Orthopedics and Sports Medicine

Reference19 articles.

1. Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030;Kurtz;J Bone Joint Surg Am,2007

2. Internal validation of a predictive model for satisfaction after primary total knee arthroplasty;Kunze;J Arthroplasty,2019

3. Internal validation of a predictive model for complications after total hip arthroplasty;Kunze;J Arthroplasty,2018

4. Cost analysis and bundled care of hip and knee replacement;Kee;J Surg Orthop Adv,2019

5. Bundled payments in total joint replacement: keeping our care affordable and high in quality;McLawhorn;Curr Rev Musculoskelet Med,2017

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