An Electronic Medical Record–Based Discharge Disposition Tool Gets Bundle Busted: Decaying Relevance of Clinical Data Accuracy in Machine Learning

An Electronic Medical Record–Based Discharge Disposition Tool Gets Bundle Busted: Decaying Relevance of Clinical Data Accuracy in Machine Learning

Background: Determining discharge disposition after total joint arthroplasty (TJA) has been a challenge. Advances in machine learning (ML) have produced computer models that learn by example to generate predictions on future events. We hypothesized a trained ML algorithm’s diagnostic accuracy will b...

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Bibliographic Details
Main Authors: Alexander S. Greenstein, MD, Jack Teitel, MS, David J. Mitten, MD, Benjamin F. Ricciardi, MD, Thomas G. Myers, MD, MPT
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:Arthroplasty Today
Subjects:
Machine learning
Artificial intelligence
Arthroplasty
Discharge
Online Access:http://www.sciencedirect.com/science/article/pii/S2352344120301722

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