文献
J-GLOBAL ID:201902260159933973
整理番号:19A2818225
心血管血流モデリングにおける機械学習:物理学情報化ニューラルネットワークを用いた非侵襲的4DフローMRIデータからの動脈血圧の予測【JST・京大機械翻訳】
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks
著者 (6件):
Kissas Georgios
(Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA, USA)
,
Yang Yibo
(Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA, USA)
,
Hwuang Eileen
(Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA)
,
Witschey Walter R.
(Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA)
,
Detre John A.
(Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA)
,
Perdikaris Paris
(Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA, USA)
資料名:
Computer Methods in Applied Mechanics and Engineering
(Computer Methods in Applied Mechanics and Engineering)
巻:
358
ページ:
Null
発行年:
2020年
JST資料番号:
E0856A
ISSN:
0045-7825
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)