Keita Sato

Reverse-engineering the diagnostic process: An indirect finding-driven deep learning model for pelvic active bleeding detection on CT that achieves specialist-level performance and surpasses residents - a multicenter study.

Contrast-enhanced computed tomography (CT) is useful for detecting active bleeding in patients with pelvic trauma. However, early detection of active bleeding from CT images is challenging due to the extensive image volume, which can delay intervention. Although the development of accurate and rapid detection support s...