Development and validation of models for detection of postoperative infections using structured electronic health records data and machine learning

Postoperative infections constitute more than half of all postoperative complications. Surveillance of these complications is primarily done through manual chart review, which is time consuming, expensive, and typically only covers 10% to 15% of all operations. Automated surveillance would permit th...

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Veröffentlicht in:	Surgery 2023-02, Vol.173 (2), p.464-471
Hauptverfasser:	Colborn, Kathryn L., Zhuang, Yaxu, Dyas, Adam R., Henderson, William G., Madsen, Helen J., Bronsert, Michael R., Matheny, Michael E., Lambert-Kerzner, Anne, Myers, Quintin W.O., Meguid, Robert A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Electronic Health Records Humans Machine Learning Postoperative Complications - diagnosis Postoperative Complications - epidemiology Retrospective Studies Surgical Wound Infection - diagnosis Surgical Wound Infection - epidemiology Urinary Tract Infections - diagnosis Urinary Tract Infections - epidemiology
Online-Zugang:	Volltext
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