A multicenter study to develop a non-invasive radiomic model to identify urinary infection stone in vivo using machine-learning
Junjiong Zheng, Hao Yu, Jesur Batur, Zhenfeng Shi, Aierken Tuerxun, Abudukeyoumu Abulajiang, Sihong Lu, Jianqiu Kong, Lifang Huang, Shaoxu Wu, Zhuo Wu, Ya Qiu, Tianxin Lin, Xiaoguang Zou
Topics & Concepts
In vivoUrinary systemMedicineMulticenter studyMachine learningComputer scienceMedical physicsUrologyArtificial intelligencePathologyInternal medicineBiologyBiotechnologyRandomized controlled trialAdvanced X-ray and CT ImagingKidney Stones and Urolithiasis TreatmentsDiverticular Disease and Complications