Development and internal validation of machine learning algorithms to predict patient satisfaction after total hip arthroplasty

Development and internal validation of machine learning algorithms to predict patient satisfaction after total hip arthroplasty

Abstract Background Patient satisfaction is a unique and important measure of success after total hip arthroplasty (THA). Our study aimed to evaluate the use of machine learning (ML) algorithms to predict patient satisfaction after THA. Methods Prospectively collected data of 1508 primary THAs perfo...

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Bibliographic Details
Main Authors: Siyuan Zhang, Jerry Yongqiang Chen, Hee Nee Pang, Ngai Nung Lo, Seng Jin Yeo, Ming Han Lincoln Liow
Format: Article
Language:English
Published: BMC 2021-09-01
Series:Arthroplasty
Subjects:
Machine learning
Artificial intelligence
Total hip arthroplasty
Satisfaction
Patient-reported outcome measures
Online Access:https://doi.org/10.1186/s42836-021-00087-3

Internet

https://doi.org/10.1186/s42836-021-00087-3

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