Using Multi-Task Learning-Based Framework to Detect ST-Segment and J-Point Deviation From Holter

Using Multi-Task Learning-Based Framework to Detect ST-Segment and J-Point Deviation From Holter

Artificial intelligence is increasingly being used on the clinical electrocardiogram workflows. Few electrocardiograms based on artificial intelligence algorithms have focused on detecting myocardial ischemia using long-term electrocardiogram data. A main reason for this is that interference signals...

Full description

Bibliographic Details
Main Authors: Shuang Wu, Qing Cao, Qiaoran Chen, Qi Jin, Zizhu Liu, Lingfang Zhuang, Jingsheng Lin, Gang Lv, Ruiyan Zhang, Kang Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Physiology
Subjects:
holter
electrocardiogram
ST-Segment
deep learning
multi-task learning
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2022.912739/full

Internet

https://www.frontiersin.org/articles/10.3389/fphys.2022.912739/full

Similar Items