Performance of machine learning algorithms for surgical site infection case detection and prediction: A systematic review and meta-analysis

BACKGROUND: Medical researchers and clinicians have shown much interest in developing machine learning (ML) algorithms to detect/predict surgical site infections (SSIs). However, little is known about the overall performance of ML algorithms in predicting SSIs and how to improve the algorithm's...

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Detalles Bibliográficos
Autores principales: Wu, Guosong, Khair, Shahreen, Yang, Fengjuan, Cheligeer, Cheligeer, Southern, Danielle, Zhang, Zilong, Feng, Yuanchao, Xu, Yuan, Quan, Hude, Williamson, Tyler, Eastwood, Cathy A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Systematic Review / Meta-analysis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9793260/
https://www.ncbi.nlm.nih.gov/pubmed/36582918
http://dx.doi.org/10.1016/j.amsu.2022.104956

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9793260/
https://www.ncbi.nlm.nih.gov/pubmed/36582918
http://dx.doi.org/10.1016/j.amsu.2022.104956

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