Oral Session
Urogenital＜Oral＞

[OS05-6] Radiomic machine learning for assessment of risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion

^○Satoshi Otani^1,2, Yuki Himoto¹, Mizuho Nishio³, Koji Fujimoto⁴, Yusaku Moribata⁵, Masahiro Yakami⁶, Yasuhisa Kurata¹, Junzo Hamanishi⁷, Akihiko Ueda⁷, Sachiko Minamiguchi⁸, Masaki Mandai⁷, Aki Kido¹, Ryota Fujimoto², Yuji Nakamoto¹ (1.Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 2.Department of Radiology, Kyoto City Hospital, 3.Department of Radiology, Kobe University, 4.Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, 5.Department of Diagnostic Radiology, Shiga General Hospital, 6.Preemptive Medicine and Lifestyle-related Disease Research Center, Kyoto University Hospital, 7.Department of Gynecology and Obstetrics, Kyoto University, 8.Department of Diagnostic Pathology, Kyoto University)