Session Details
[CDSY1]Cross-disciplinary Symposium 1 Application of artificial intelligence to cardiovascular and thoracic surgery
Tue. Oct 20, 2026 8:00 AM - 9:30 AM JST
Tue. Oct 20, 2026 11:00 PM - 12:30 AM UTC
Tue. Oct 20, 2026 11:00 PM - 12:30 AM UTC
Room 2 (Room A, 2F, Kyoto International Conference Center)
Chairperson: Takeo Fujita (: Norihiko Ikeda(Graduate School, International University of Health and Welfare), Shingo Kasahara (Department of Cardiovasccular Surgery, Okayama University), Takeo Fujita (Division of Esophageal Surgery, National Cancer Center Hospital East)
[CDSY1-1]Revolutionizing VAD Management with Artificial Intelligence
Tatsuki Fujiwara, Eiki Nagaoka, Takuya Kawabata, Naoki Tadokoro, Hironobu Sakurai, Junya Nabeshima, Takuro Takashima, Takushi Akada, Yuki Okumura, Naoshi Itou, Tomoyuki Fujita (Department of Cardiovascular Surgery, Institute of Science Tokyo)
[CDSY1-2]Development of an AI-Based Prognostic Model for Lung Cancer and Its Potential Application in Patients After Neoadjuvant Chemoimmunotherapy
Tomoyoshi Takenaka1,2, Fumihiko Kinoshita1,2, Kotaro Matsumoto3, Takanori Yamashita4, Naoya Iwamoto2, Taichi Matsubara1,2, Kazuki Takada1,2, Naoki Makashima3, Tomoharu Yoshizumi1 (1.Department of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, 2.Department of Thracic Surgery, Kyushu University Hospital, 3.Department of Health Care Administration and Management, Graduate School of Medical Sciences, Kyushu University, 4.Medical Information Center, Kyushu University Hospital)
[CDSY1-3]Development of an AI navigation system for minimally invasive esophagectomy
Masashi Takeuchi1,2, Yosuke Morimoto1, Kazuaki Matsui1, Hirofumi Kawakubo1, Satoru Matsuda1 (1.Department of Surgery, Keio University, 2.Direava inc.)
[CDSY1-4]AI-Assisted Semi-Automated Volumetric Quantification of Acute Type B Aortic Dissection Reveals Pattern-Specific Remodeling Beyond Diameter Assessment
Taro Kuroda, Akihiro Yoshitake, Takayuki Gyoten, Keitaro Doumae, Yuko Gatate, Mio Kasai, Tatsuo Takahashi, Ryu Inoue, Yuto Hori, Kaito Masuda, Nobutaka Kikuchi, Kazuki Saito (Department of Cardiovascular Surgery, Saitama Medical University International Medical Center)
[CDSY1-5]Clinical Utility of AI-Based Prognostic Models in Cardiovascular Surgery: Development and Comparison of Machine Learning Models for Medium- to Long-Term Prediction After Open-Heart Surgery
Shusuke Arai1, Jun Hayashi2, Yoshinori Kuroda1, Masahiro Mizumoto1, Ken Nakamura1, Shuto Hirooka1, Tomonori Ochiai1, Tetsuro Uchida1 (1.Department of Cardiovascular, Thoracic and Pediatric Surgery, Faculty of Medicine, Yamagata University, 2.Nihonkai General Hospital)
[CDSY1-6]Utility of Integrated Generative AI/VR/3D Image Surgical Simulation Platform — Application to Minimally Invasive Cardiac Surgery —
Kazutoshi Tachibana1,2, Ikuma Sato2, Merlini Mcandrew1, Tomoya Oshiro1, Hidenobu Akamatsu1, Shingo Osaki1, Suguru Tatsuki1, Naohiro Wakabayashi1, Gentaku Hama1, Yosuke Kuroda1, Keijiro Mitusbe1 (1.Department of Cardiovascular Surgery, Sapporo Cardiovascular Clinic, 2.Future University Hakodate)
[CDSY1-7]Generative AI-Driven, Surgeon-Led Development of a Surgical Support System: Implementation and Future Prospects of the da Vinci 3D-TilePro Stereoscopic Navigation "i-Lung 3D Simulator"
Naoya Kawakita, Ayaka Tsuji, Shiori Matusi, Kazumasa Nanjyo, Emi Takehara, Kiyoshige Yamamoto, Taihei Takeuchi, Keisuke Fujimoto, Naoki Miyamoto, Atsushi Morishita, Hiroaki Toba, Hiromitsu Takizawa (Department of Thoracic and Endocrine Surgery and Oncology, Institute of Biomedical Sciences, The University of Tokushima Graduate School)
[CDSY1-8]Artificial Intelligence–Based Survival Modeling for Virtual Surgical Selection in Lung Cancer: Is it possible to determine individual selection of sublobar resections?
Ichiro Yoshino1,2, Yuichi Sakairi2,4, Eiryo Kawakami3, Hidemi Suzuki2, Yukio Sato5, Masayuki Chida6, Shinichi Toyooka7, Shunichi Watanabe8, Hiroshi Date9,10, Yasushi Shintani11 (1.Department of Thoracic Surgery, International University of Health and Welfare Narita Hospital, 2.Department of General Thoracic Surgery, Chiba University, 3.Department of Artifical Intelligence Medicine, Chiba University, 4.Department of Thoracic Surgery, Chiba Cancer Center, 5.Department of Thoracic Surgery, University of Tsukuba, 6.Department of General Thoracic Surgery, Dokkyo Medical University, 7.Department of General Thoracic Surgery, Okayama University, 8.Department of Thoracic Surgery, National Cancer Center Hospital, 9.Department of Thoracic Surgery, Kyoto University, 10.Department of Thoracic and Cardiovascular Surgery, Duku University, 11.Department of General Thoracic Surgery, The University of Osaka)
[CDSY1-9]Feasibility of an AI-based intraoperative No-Go zone guidance model for robotic-assisted lung cancer surgery
Kenta Nakahashi1, Takuto Yoshida2, Matjaz Jogan3, Takahiro Yanagihara1, Fumi Yokote1, Kate Kazlovich1, Andrew Effat1, Guiqiu Liao3, Hana Kosoy1, Nicholas Bernards1, Doraid Jarrar4, Daniel Hashimoto3, Amin Madani2, Kazuhiro Yasufuku1,2 (1.Division of Thoracic Surgery, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada, 2.Department of Surgery, University of Toronto, Toronto, Ontario, Canada, 3.Department of Surgery, University of Pennsylvania, Philadelphia, USA, 4.Division of Thoracic Surgery, Hospital of the University of Pennsylvania, Philadelphia, USA)
