Random forest identifies predictors of discharge destination following total shoulder arthroplasty

Random forest identifies predictors of discharge destination following total shoulder arthroplasty

Background: Machine learning algorithms are finding increasing use in prediction of surgical outcomes in orthopedics. Random forest is one of such algorithms popular for its relative ease of application and high predictability. In the process of sample classification, algorithms also generate a list...

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Bibliographic Details
Main Authors: Jun Ho Chung, MD, Damien Cannon, MD, Matthew Gulbrandsen, MD, Dheeraj Yalamanchili, MD, Wesley P. Phipatanakul, MD, Joseph Liu, MD, Anirudh Gowd, MD, Anthony Essilfie, MD
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:JSES International
Subjects:
Machine Learning
Random forest
shoulder arthroplasty
surgical outcomes
Online Access:http://www.sciencedirect.com/science/article/pii/S2666638323001093

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http://www.sciencedirect.com/science/article/pii/S2666638323001093

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