Evening, October 13, 2019
Venue: main conference venue, InterContinental Shenzhen, Shenzhen, China
Address: No. 9009 Shennan Road, Overseas Chinese Town : Shenzhen , 518053, China
According to the latest statistics of World Health Organization, cardiovascular disease remains the leading cause of death globally. During the last decade, its mortality rate is still the highest among all diseases (like tumors). With the fast development of machine learning (AI) techniques and vast amount of medical data, physicians and machine learning scientists can work together to enable AI capability in the diagnosis and treatment of cardiovascular diseases. This workshop will bring together physicians, technicians and machine learning scientists to discuss the latest progressions.
All accepted papers will be included as a joint proceeding with MICCAI 2019.
The Call for Paper brochure can be downloaded here.
Authors are invited to submit full-length high-quality papers (up to 8-pages). Papers covering theory and/or application areas of machine learning and medical engineering for cardiovascular health are invited for submission. Submitted papers will be refereed on their originality, presentation, empirical results, and quality of evaluation.
The workshop submission deadline will be 23:59, Beijing Time, 15 July, 2019. There will be no extension. Papers are submitted electronically (LNCS style, double blind review) to the EasyChair system. Please refer to the Author Guidelines for instructions on paper formats. Registration: Please refer to the MICCAI 2019 website.
|Guijin Wang||Tsinghua University, China|
|Feng Zhang||Chinese Academy of Sciences, China|
|Yongpan Liu||Tsinghua University, China|
|Jinghao Xue||University College London, UK|
|Zijian Ding||Tsinghua University, China|
|Chengquan Li||Tsinghua University, China|
|Ping Zhang||Beijing Tsinghua Changgung Hospital, China|
|Haiyi Liu||Beijing Tsinghua Changgung Hospital, China|
|Dapeng Fu||Beijing Zhongguancun Hospital, China|
|Yuan He||Beijing Tongren Hospital, CMU, China|
|Fang Luo||Fuwai Hospital & National Center for Cardiovascular Diseases, China|
Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using
Enhanced Deep Convolutional Neural Networks
Binhang Yuan, Wenhui Xing
An Ensemble Neural Network for Multi-label Classification of
Dongya Jia, Wei Zhao, Zhenqi Li, Cong Yan, Hongmei Wang, Jing Hu, Jiansheng Fang
Multi-label classification of abnormalities in 12-lead ECG using 1D CNN and
Chengsi Luo, Hongxiu Jiang, Quanchi Li and Nini Rao
|Poster Session||30min (Wth Coffee Break)|
Particle Swarm Optimization for Great Enhancement in Semi-Supervised Retinal
Vessel Segmentation with Generative Adversarial Networks
Qiang Huo, Geyu Tang, and Feng Zhang
Deep Learning to Improve Heart Disease Risk Prediction
Shelda Sajeev, Anthony Maeder, Stephanie Champion, Alline Beleigoli, Cheng Ton, Xianglong Kong, and Minglei Shu
Attention-Guided Decoder in Dilated Residual Network for Accurate Aortic
Valve Segmentation in 3D CT Scans
Bowen Fan, Naoki Tomii, Hiroyuki Tsukihara, Eriko Maeda, Haruo Yamauchi, Kan Nawata, Asuka Hatano, Shu Takagi, Ichiro Sakuma and Minoru Ono
Dr. Yiyu Shi is currently an associate professor in the Department of Computer Science at the University of Notre Dame, and the director of Sustainable Computing Lab (SCL).
Guoxing Wang (Shang Hai Jiao Tong University) Confirmed Dr. Guoxing Wang is currently an associate professor in the School of Microelectronics at Shanghai Jiao Tong University.
Dr. Fang Luo is currently deputy chief physician of the Department of Endocrinology and Cardiovascular Metabolism, Fuwai Hospital of Chinese Academy of Medical Sciences.