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| Machine Learning for Antibiotic Resistance Prediction: A Prototype Using Off-the-Shelf Techniques and Entry-Level Data to Guide Empiric Antimicrobial Therapy |
| 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 |
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Healthc Inform Res. 2021;27(3):214-221. Published online July 31, 2021 DOI: https://doi.org/10.4258/hir.2021.27.3.214 |
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Machine Learning for Antibiotic Resistance Prediction: A Prototype Using Off-the-Shelf Techniques and Entry-Level Data to Guide Empiric Antimicrobial Therapy Healthcare Informatics Research. 2021;27(3):214-221  Using machine learning to predict antibiotic resistance to support optimal empiric treatment of urinary tract infections Antimicrobial Stewardship & Healthcare Epidemiology. 2022;2(S1):s69-s69 A1.32 Bacterial spectrum and antibiotic resistance of uropathogens in hospitalized urological patients with urinary tract infections (1994–2004) and consequences for empiric antibiotic therapy International Journal of Antimicrobial Agents. 2005;26:S75-S76 Prediction of Autism spectrum disorder from high dimensional data using Machine Learning Techniques . 2023; Chronic kidney disease prediction using machine learning techniques Journal of Big Data. 2022;9(1): Multi-Level Driver Workload Prediction using Machine Learning and Off-the-Shelf Sensors Transportation Research Record: Journal of the Transportation Research Board. 2018;2672(37):141-152 Antimicrobial resistance: improving antibiotic stewardship by multi-disciplinary learning JAC-Antimicrobial Resistance. 2019;1(2): Copyright Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques. 2019;iv Machine learning techniques Practical Machine Learning for Data Analysis Using Python. 2020;91-202 Preface Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques. 2019;ix |
