Logistic Regression and Machine Learning Models Cannot Discriminate Between Satisfied and Dissatisfied Total Knee Arthroplasty Patients
Author:
Publisher
Elsevier BV
Subject
Orthopedics and Sports Medicine
Reference29 articles.
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2. Patient dissatisfaction following total knee arthroplasty: a systematic review of the literature;Gunaratne;J Arthroplasty,2017
3. Hip and Knee Replacements in Canada: CJRR Annual Statistics Summary,2018
4. Predictors of patient satisfaction following primary total knee arthroplasty: results from a Traditional statistical model and a machine learning algorithm;Farooq;J Arthroplasty,2020
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1. Analgesic Effect of Intraoperative Intravenous S(+)-Ketamine During Total Knee Arthroplasty Surgery: Study Protocol for a Randomized Controlled Clinical Trial;JMIR Research Protocols;2023-12-08
2. The development of machine learning algorithms that can predict patients satisfaction using baseline characteristics, and preoperative and operative factors of total knee arthroplasty;The Knee;2023-10
3. A role for artificial intelligence applications inside and outside of the operating theatre: a review of contemporary use associated with total knee arthroplasty;Arthroplasty;2023-07-04
4. Predicting 30-day readmission following total knee arthroplasty using machine learning and clinical expertise applied to clinical administrative and research registry data in an Australian cohort;Arthroplasty;2023-06-01
5. Established and Novel Risk Factors for 30-Day Readmission Following Total Knee Arthroplasty: A Modified Delphi and Focus Group Study to Identify Clinically Important Predictors;Journal of Clinical Medicine;2023-01-17
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