Usefulness of machine learning models in differentiating malignant from benign breast tumors using diffusion-weighted images

Toshiki Yamasaki

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Oral Session

Oral Session
Breast ＜Oral＞

Sat. Sep 10, 2022 8:30 AM - 9:20 AM Room 3 (Nagoya Congress Center, Bldg. 2, 1F, Exhibiton Room 211+212)

Chairs: Hiroko Satake（Department of Radiology, Nagoya University Hospital）, Mariko Goto（Department of Radiology, Kyoto Prefectural University of Medicine）

[OS08-2] Usefulness of machine learning models in differentiating malignant from benign breast tumors using diffusion-weighted images

^○Toshiki Yamasaki¹, Mami Iima^2,3, Ryosuke Mizuno⁴, Masako Kataoka², Aika Okazawa², Masakazu Toi⁵, Yuji Nakamoto² (1.Kyoto University Faculty of Medicine, 2.Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 3.Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital, 4.A.I. System Research CO.,Ltd, 5.Department of Breast Surgery, Kyoto University Graduate School of Medicine)

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Presentation information

Oral SessionBreast ＜Oral＞

[OS08-2] Usefulness of machine learning models in differentiating malignant from benign breast tumors using diffusion-weighted images

Password

Oral Session
Breast ＜Oral＞