Gender-Specific Machine Learning Models to Predict Unplanned Return to Operating Room Following Primary Total Shoulder Arthroplasty-Reference-Cited by-同舟云学术

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Gender-Specific Machine Learning Models to Predict Unplanned Return to Operating Room Following Primary Total Shoulder Arthroplasty

Published:2023-06-26 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 11th International Conference on Healthcare Informatics (ICHI)
language:
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Author:

Letter Christina¹,Gupta Puneet²,Kim Annie¹,Cong Guang-Ting³,Liu Hongfang⁴,Tafti Ahmad P.¹

Affiliation:

1. University of Pittsburgh,School of Health and Rehabilitation Sciences,Pittsburgh,PA,USA

2. George Washington University,Department of Orthopaedic Surgery,Washington,DC,USA

3. University of Pittsburgh Medical Center,Department of Orthopaedic Surgery,Pittsburgh,PA,USA

4. Mayo Clinic,Department of Artificial Intelligence and Informatics,Rochester,MN,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10336927/10336922/10337172.pdf?arnumber=10337172

Reference18 articles.

1. Comparison of machine learning techniques to predict unplanned readmission following total shoulder arthroplasty

2. Characteristics and risk factors for 90-day readmission following shoulder arthroplasty

3. Understanding risk for early dislocation resulting in reoperation within 90 days of reverse total shoulder arthroplasty: extreme rare event detection through cost-sensitive machine learning

4. Reoperation after primary anatomic total shoulder arthroplasty;Robinson;Journal of Shoulder and Elbow Surgery,2020

5. Early aseptic reoperation after shoulder arthroplasty increases risk of subsequent prosthetic joint infection

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