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A multicenter study to develop a non-invasive radiomic model to identify urinary infection stone in vivo using machine-learning

UrologyEngineeringMachine LearningMedical ImagingBiomedical ImagingDiagnosisUrinary Infection StoneNon-invasive Radiomic ModelInnovative DiagnosticsComputer-aided DiagnosisBiostatisticsRadiomicsMulticenter StudyMedical Image ComputingPublic HealthHealth InformaticsRadiology