Machine Learning for Antibiotic Resistance Prediction: A Prototype Using Off-the-Shelf Techniques and Entry-Level Data to Guide Empiric Antimicrobial Therapy

OBJECTIVES: In the era of increasing antimicrobial resistance, the need for early identification and prompt treatment of multi-drug-resistant infections is crucial for achieving favorable outcomes in critically ill patients. As traditional microbiological susceptibility testing requires at least 24...

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Detalles Bibliográficos
Autores principales: Feretzakis, Georgios, Sakagianni, Aikaterini, Loupelis, Evangelos, Kalles, Dimitris, Skarmoutsou, Nikoletta, Martsoukou, Maria, Christopoulos, Constantinos, Lada, Malvina, Petropoulou, Stavroula, Velentza, Aikaterini, Michelidou, Sophia, Chatzikyriakou, Rea, Dimitrellos, Evangelos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369050/
https://www.ncbi.nlm.nih.gov/pubmed/34384203
http://dx.doi.org/10.4258/hir.2021.27.3.214

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369050/
https://www.ncbi.nlm.nih.gov/pubmed/34384203
http://dx.doi.org/10.4258/hir.2021.27.3.214

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