Using Machine-Learned Bayesian Belief Networks to Predict Perioperative Risk of Clostridium Difficile Infection Following Colon Surgery

BACKGROUND: Clostridium difficile (C-Diff) infection following colorectal resection is an increasing source of morbidity and mortality. OBJECTIVE: We sought to determine if machine-learned Bayesian belief networks (ml-BBNs) could preoperatively provide clinicians with postoperative estimates of C-Di...

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Detalles Bibliográficos
Autores principales: Steele, Scott, Bilchik, Anton, Eberhardt, John, Kalina, Philip, Nissan, Aviram, Johnson, Eric, Avital, Itzhak, Stojadinovic, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications Inc. 2012
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626137/
https://www.ncbi.nlm.nih.gov/pubmed/23611947
http://dx.doi.org/10.2196/ijmr.2131

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626137/
https://www.ncbi.nlm.nih.gov/pubmed/23611947
http://dx.doi.org/10.2196/ijmr.2131

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