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Using machine learning techniques to predict antimicrobial resistance in stone disease patients

Lazaros Tzelves, Lazaros Lazarou, Georgios Feretzakis, Dimitris Kalles, Panagiotis Mourmouris, Evangelos Loupelis, Spyridon P. Basourakos, Marinos Berdempes, Ioannis Manolitsis, Iraklis Mitsogiannis, Andreas Skolarikos, Ioannis Varkarakis

2022World Journal of Urology33 citationsDOI

Topics & Concepts

Artificial intelligenceGram stainingMedicineReceiver operating characteristicMachine learningLogistic regressionAntibioticsClassifier (UML)Antibiotic resistanceInternal medicineComputer scienceMicrobiologyBiologyUrinary Tract Infections ManagementBacterial Identification and Susceptibility TestingSurgical site infection prevention
Using machine learning techniques to predict antimicrobial resistance in stone disease patients | Litcius