Artificial Neural Networks Predict 30-Day Mortality After Hip Fracture: Insights From Machine Learning.

Journal: The Journal of the American Academy of Orthopaedic Surgeons

Published Date: Nov 15, 2021

Abstract

OBJECTIVES: Accurately stratifying patients in the preoperative period according to mortality risk informs treatment considerations and guides adjustments to bundled reimbursements. We developed and compared three machine learning models to determine which best predicts 30-day mortality after hip fracture.

Authors

Malcolm R DeBaun

From the Department of Orthopaedic Surgery, Stanford University Medical Center, Palo Alto, CA.
Gustavo Chavez
Andrew Fithian
Kingsley Oladeji
Noelle Van Rysselberghe
L Henry Goodnough
Julius A Bishop
Michael J Gardner

Keywords

Bayes Theorem Female Hip Fractures Humans Logistic Models Machine Learning Male Neural Networks, Computer

External Resources

View on PubMed Access via DOI PubMed (33315645)

Artificial Neural Networks Predict 30-Day Mortality After Hip Fracture: Insights From Machine Learning.

Abstract

Authors

Keywords

External Resources

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