Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data

This study describes a novel approach to solve the surgical site infection (SSI) classification problem. Feature engineering has traditionally been one of the most important steps in solving complex classification problems, especially in cases with temporal data. The described novel approach is base...

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Detalles Bibliográficos
Autores principales: Kocbek, Primoz, Fijacko, Nino, Soguero-Ruiz, Cristina, Mikalsen, Karl Øyvind, Maver, Uros, Povalej Brzan, Petra, Stozer, Andraz, Jenssen, Robert, Skrøvseth, Stein Olav, Stiglic, Gregor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399553/
https://www.ncbi.nlm.nih.gov/pubmed/30915154
http://dx.doi.org/10.1155/2019/2059851

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399553/
https://www.ncbi.nlm.nih.gov/pubmed/30915154
http://dx.doi.org/10.1155/2019/2059851

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