Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Primary Anatomic Total Shoulder Replacements

Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Primary Anatomic Total Shoulder Replacements

Background The demand and incidence of anatomic total shoulder arthroplasty (aTSA) procedures is projected to increase substantially over the next decade. There is a paucity of accurate risk prediction models which would be of great utility in minimizing morbidity and costs associated with major pos...

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Bibliographic Details
Main Authors: Sai K Devana, Akash A Shah, Changhee Lee, Andrew R Jensen, Edward Cheung, Mihaela van der Schaar, Nelson F SooHoo
Format: Article
Language:English
Published: SAGE Publishing 2022-04-01
Series:Journal of Shoulder and Elbow Arthroplasty
Online Access:https://doi.org/10.1177/24715492221075444

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