Building a Risk Prediction Model for Postoperative Pulmonary Vein Obstruction via Quantitative Analysis of CTA Images

Author:

Pei Yuchen1ORCID,Shi Guocheng2,Xia Wenjin1,Wen Chen2ORCID,Sun Dazhen1,Zhu Fang2ORCID,Li Jiang1,Zhu Zhongqun2,Liu Xiaoqing3,Huang Meiping4,Wang Yu-Ping5ORCID,Chen Huiwen2,Wang Lisheng1ORCID

Affiliation:

1. Department of Automation, Shanghai Jiao Tong University, Shanghai, China

2. Department of Cardiothoracic Surgery, Congenital Heart Center, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China

3. Deepwise AI Lab, Beijing, China

4. Department of Catheterization Lab, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

5. Biomedical Engineering Department, Tulane University, New Orleans, LA, USA

Funder

National Natural Science Foundation of China

School of Medicine, Shanghai Jiao Tong University

Shanghai Municipal Science and Technology Major Project

Shanghai Jiao Tong University Translational Medicine Cross Research Funds

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Cardiac Deep Learning Model for Congenital Heart Disease Recognition;2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA);2023-12-08

2. A Cardiac Deep Learning Model (CDLM) to Predict and Identify the Risk Factor of Congenital Heart Disease;Diagnostics;2023-06-28

3. Anatomical attention-based prediction of postoperative pulmonary venous obstruction via CTA images;Computerized Medical Imaging and Graphics;2023-01

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