Artificial intelligence classification methods of atrial fibrillation with implementation technology-Reference-Cited by-同舟云学术

Artificial intelligence classification methods of atrial fibrillation with implementation technology

Published:2016-10-25 Issue:sup1 Volume:21 Page:154-161
ISSN:2469-9322
Container-title:Computer Assisted Surgery
language:en
Short-container-title:Computer Assisted Surgery

Author:

Lim Huey Woan¹,Hau Yuan Wen¹,Lim Chiao Wen²,Othman Mohd Afzan³

Affiliation:

1. IJN-UTM Cardiovascular Engineering Centre, Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia;

2. Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia;

3. Department of Electronics and Computer Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia

Publisher

Informa UK Limited

Subject

Family Practice,Computer Science Applications,Surgery

Link

https://tandfonline.com/doi/pdf/10.1080/24699322.2016.1240303

Reference46 articles.

1. Capitec Bank Holdings Ltd. Annual report. 2014. World Stroke Organization [Internet]. 2014; Available from: https://www.capitecbank.co.za/investor-relations.

2. Age, Ethnicity, and Stroke Risk in Patients With Atrial Fibrillation

3. Prevalence of Diagnosed Atrial Fibrillation in Adults

4. Age Threshold for Increased Stroke Risk Among Patients With Atrial Fibrillation

5. Atrial fibrillation is associated with an increased risk for mortality and heart failure progression in patients with asymptomatic and symptomatic left ventricular systolic dysfunction: a retrospective analysis of the SOLVD trials

Cited by 12 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. Classification of Physiological States Through Machine Learning Algorithms Applied to Ultra-Short-Term Heart Rate and Pulse Rate Variability Indices on a Single-Feature Basis;IFMBE Proceedings;2024

2. Atrial fibrillation prediction by combining ECG markers and CMR radiomics;Scientific Reports;2022-11-07

3. Detecting PVC Beats by Beat-by-beat Analysis of ECG Signals Using Machine Learning Classifiers for Real-time Predictive Cardiac Health Monitoring;2022 IEEE 13th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON);2022-10-26

4. Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring;Frontiers in Electronics;2022-07-01

5. Study on the Application of Visual Communication Design in APP Interface Design in the Context of Deep Learning;Computational Intelligence and Neuroscience;2022-06-20