日時
2017年10月30日15:00 - 16:30
講演者
水藤 寛 (東北大学 材料科学高等研究所 教授)
会場
理化学研究所 和光キャンパス RIBF棟 2階 大会議室
配信
計算科学研究棟 R511
言語
英語

第23回iTHES理論科学コロキウム

Recent rapid progress of AI technologies has strongly affected the medical community, profoundly enhancing medical image analysis as well as improving decision-making in clinical practice. Nevertheless, black-box systems cannot be accepted easily in clinical medicine because of issues related to accountability and incorporation of new and rapidly developing medical technologies.

This talk presents a bilateral approach to cardiovascular problems consisting of (1) machine learning approach for estimation of fluid dynamical forces such as wall shear stress and oscillatory shear index by using geometrical information of the vessels; and (2) simulation approach for understanding physical mechanisms, from vessel geometry to wall forces distributions via flow patterns, using fluid–structure interaction analysis based on partial differential equations. This work was conducted as part of our JST-CREST project: "New challenges for mathematical modeling in clinical medicine."