Intelligent Detection of Silent Myocardial Ischemia Dynamic Electrocardiogram Based on Deep Learning

Corresponding author: miaoyuanqing

DOI: 10.12201/bmr.202111.00009

•  

  Abstract: ECG is one of the most commonly used examinations in clinical diagnosis, which is widely used. ECG can record the electrical activity of the heart, not only assist clinical diagnosis of arrhythmia, myocardial ischemia, myocardial infarction and other diseases, but also judge the impact of drugs or electrolytes on the heart. Deep learning can be learned through training data sets, and a lot of useful information can be obtained in the learning process, which is very helpful for understanding and judging image, sound, text and other data. Based on deep learning technology, this paper proposes an algorithm to assist doctors in intelligent analysis of silent myocardial ischemia dynamic electrocardiogram, which greatly improves the accuracy of dynamic electrocardiogram analysis and reduces the misdiagnosis rate of ECG interpretation.

  Key words: deep; learning, dynamic; electrocardiogram, intelligent; analysis, silent; myocardial ischemia

  Submit time: 23 December 2021

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
• html

• 图表

• Gu Yao-wen, Li Jiao. Progress of Mining Electronic Health Records based on Unsupervised Deep Learning Methods. 2021. doi: 10.12201/bmr.202104.00013

  jinlizhu, gehui, guoqing, lishaoqiong, duxuejie. Early warning of influenza epidemics using meteorological factors and machine learning. 2021. doi: 10.12201/bmr.202012.00008

  yuqi, lijinghua. Construction and service of intelligent TCM health management cloud platform. 2021. doi: 10.12201/bmr.202108.00012

  fengli. A Comparative Study on the Accuracy of Nine Combined Machine Learning Algorithms in Early Diagnosis of Tumors Based on High-dimensional dataFeng Li 1,*, Yue Xiaofei 2. 2021. doi: 10.12201/bmr.202108.00016

  duan yong xuan, Zhen tian min, zhang rui, xi min, zhao wu, yue yuan. Research on intelligent decision service based on medical information. 2021. doi: 10.12201/bmr.202110.00014

  LUWEN, 史. Investigation and analysis of clinical nurses use of intelligent nursing information system. 2021. doi: 10.12201/bmr.202101.00011

  tangyangjie, wuxiaofeng, liuqun, ouyanglin, luoaifang. On Artificial Intelligent-aided Diagnosis of Early Lumbar Disc Degeneration. 2022. doi: 10.12201/bmr.202112.00007

  Deng Lan, Xu Jin, Du Tongzhou, Huang Lihong, Yin Shiyu. An Intelligent Nursing Scheduling Management System Based on Answer Set Programming. 2021. doi: 10.12201/bmr.202107.00020

  YuanJunYi, ShenYingJie, PanChangQing. Research on the Application of Hospital Internet Health Consultation System Based on Intelligent Guide Diagnosis. 2021. doi: 10.12201/bmr.202104.00016

• ID	Submit time	Number	Download
  1	2021-11-03	bmr.202111.00009V1	Download

• Public  Anonymous  To author only Submit Comments