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

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 h...

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Bibliographic Details
Main Authors: Georgios Feretzakis, Aikaterini Sakagianni, Evangelos Loupelis, Dimitris Kalles, Nikoletta Skarmoutsou, Maria Martsoukou, Constantinos Christopoulos, Malvina Lada, Stavroula Petropoulou, Aikaterini Velentza, Sophia Michelidou, Rea Chatzikyriakou, Evangelos Dimitrellos
Format: Article
Language:English
Published: The Korean Society of Medical Informatics 2021-07-01
Series:Healthcare Informatics Research
Subjects:
drug resistance
anti-bacterial agents
machine learning
artificial intelligence
supervised machine learning
Online Access:http://e-hir.org/upload/pdf/hir-2021-27-3-214.pdf

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http://e-hir.org/upload/pdf/hir-2021-27-3-214.pdf

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