Development of machine learning models for the detection of surgical site infections following total hip and knee arthroplasty: a multicenter cohort study

Abstract Background Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection. Methods This retrospective co...

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Bibliografische Detailangaben

Hauptverfasser:	Guosong Wu, Cheligeer Cheligeer, Danielle A. Southern, Elliot A. Martin, Yuan Xu, Jenine Leal, Jennifer Ellison, Kathryn Bush, Tyler Williamson, Hude Quan, Cathy A. Eastwood
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	BMC 2023-09-01
Schriftenreihe:	Antimicrobial Resistance and Infection Control
Schlagworte:	Surgical site infections Total hip arthroplasty Total knee arthroplasty Machine learning
Online-Zugang:	https://doi.org/10.1186/s13756-023-01294-0
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