Developing Machine Learning Algorithms to Predict Pulmonary Complications After Emergency Gastrointestinal Surgery

Objective: Investigate whether machine learning can predict pulmonary complications (PPCs) after emergency gastrointestinal surgery in patients with acute diffuse peritonitis. Methods: This is a secondary data analysis study. We use five machine learning algorithms (Logistic regression, DecisionTree...

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Detalles Bibliográficos
Autores principales: Xue, Qiong, Wen, Duan, Ji, Mu-Huo, Tong, Jianhua, Yang, Jian-Jun, Zhou, Cheng-Mao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8365303/
https://www.ncbi.nlm.nih.gov/pubmed/34409047
http://dx.doi.org/10.3389/fmed.2021.655686

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8365303/
https://www.ncbi.nlm.nih.gov/pubmed/34409047
http://dx.doi.org/10.3389/fmed.2021.655686

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