慶應義塾大学 · 医学
Takeuchi教授の研究室は、消化器がんの治療における画像診断・手術支援技術の高度化を柱としています。特に、体マスの内臓脂肪面積（VFA）が消化管接着部漏れや术后感染症の予測に有効であることを示し、手術中の個別化されたリスク管理の可能性を追求しています。また、人工知能（AI）を活用した内 endoscopy やCT画像の自動診断、さらには手術支援のためのリアルタイム対話型システムの開発にも取り組んでおり、手術の精度と効率の向上をめざしています。
Figures are computed from collected data and may differ slightly.
High VFA is more useful than BMI in predicting anastomotic leakage and SSI after total gastrectomy. Therefore, we should consider the VFA value during surgery.
Artificial intelligence (AI) has a significant impact on the field of health care, particularly imaging and video analyses. It can considerably support clinical decision-making, including the automatic diagnosis of gastrointestinal cancer during endoscopy and automated detection of pulmonary lesions on computed tomography (CT).1, 2 In the future, AI may provide innovative solutions that improve surgical efficiency and patient outcomes in the field of surgical procedures. Integrating AI into surg
If a dialog system can respond to the user as reasonable as a human, the interaction will become smoother. Timing of response such as backchannels and turn-taking plays important role in such a smooth dialog as in human-human interaction. We are now developing a dialog system which can generate response timing in real time. In this paper, we introduce a response timing generator for such a dialog system. First, we analyzed conversations between two persons and extracted prosodic and linguistic i
Surgical management was conducted adequately through the organized efforts of the entire surgery department in our country even in a pandemic during which medical resources and staff may have been limited.
DCF and subsequent esophagectomy achieved R0 resection in 50% of the patients and was associated with better long-term oncological outcomes in patients with initially unresectable esophageal cancer if their systemic status is acceptable.
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