This paper is in the following e-collection/theme issue:

Machine Learning (1501) Wearable Devices and Sensors (903) Decision Support for Health Professionals (1210) Clinical Information and Decision Making (1434) Fitness Trackers and Smart Pedometers/Accelerometers (571) Novel Sensors and Data Acquisition Methods in Cardiology (200) Electronic Health Records (1068) Memory (45)

Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18803, first published .
TOP-Net Prediction Model Using Bidirectional Long Short-term Memory and Medical-Grade Wearable Multisensor System for Tachycardia Onset: Algorithm Development Study

TOP-Net Prediction Model Using Bidirectional Long Short-term Memory and Medical-Grade Wearable Multisensor System for Tachycardia Onset: Algorithm Development Study

TOP-Net Prediction Model Using Bidirectional Long Short-term Memory and Medical-Grade Wearable Multisensor System for Tachycardia Onset: Algorithm Development Study

Authors of this article:

Xiaoli Liu1 Author Orcid Image ;   Tongbo Liu2 Author Orcid Image ;   Zhengbo Zhang3, 4 Author Orcid Image ;   Po-Chih Kuo5 Author Orcid Image ;   Haoran Xu6 Author Orcid Image ;   Zhicheng Yang7 Author Orcid Image ;   Ke Lan8 Author Orcid Image ;   Peiyao Li9 Author Orcid Image ;   Zhenchao Ouyang10 Author Orcid Image ;   Yeuk Lam Ng11 Author Orcid Image ;   Wei Yan12 Author Orcid Image ;   Deyu Li1 Author Orcid Image
Article Authors Cited by (17) Tweetations (1) Metrics

Journals

  1. Lee S, Chu Y, Ryu J, Park Y, Yang S, Koh S. Artificial Intelligence for Detection of Cardiovascular-Related Diseases from Wearable Devices: A Systematic Review and Meta-Analysis. Yonsei Medical Journal 2022;63(Suppl):S93 View
  2. Liu X, DuMontier C, Hu P, Liu C, Yeung W, Mao Z, Ho V, Thoral P, Kuo P, Hu J, Li D, Cao D, Mark R, Zhou F, Zhang Z, Celi L, Lipsitz L. Clinically Interpretable Machine Learning Models for Early Prediction of Mortality in Older Patients with Multiple Organ Dysfunction Syndrome: An International Multicenter Retrospective Study. The Journals of Gerontology: Series A 2023;78(4):718 View
  3. Moshawrab M, Adda M, Bouzouane A, Ibrahim H, Raad A. Smart Wearables for the Detection of Cardiovascular Diseases: A Systematic Literature Review. Sensors 2023;23(2):828 View
  4. Liao J, Liu L, Duan H, Huang Y, Zhou L, Chen L, Wang C. Using a Convolutional Neural Network and Convolutional Long Short-term Memory to Automatically Detect Aneurysms on 2D Digital Subtraction Angiography Images: Framework Development and Validation. JMIR Medical Informatics 2022;10(3):e28880 View
  5. Viderman D, Abdildin Y, Batkuldinova K, Badenes R, Bilotta F. Artificial Intelligence in Resuscitation: A Scoping Review. Journal of Clinical Medicine 2023;12(6):2254 View
  6. Sundrani S, Chen J, Jin B, Abad Z, Rajpurkar P, Kim D. Predicting patient decompensation from continuous physiologic monitoring in the emergency department. npj Digital Medicine 2023;6(1) View
  7. Chang P, Li H, Quan S, Lu S, Wung S, Roveda J, Li A. A transformer-based diffusion probabilistic model for heart rate and blood pressure forecasting in Intensive Care Unit. Computer Methods and Programs in Biomedicine 2024;246:108060 View
  8. Karatas T, Tortum F. Yapay Zekâ Eşliğinde Kardiak Arreste Yaklaşım Sağ Kalım Oranını Artırır mı? Nörolojik Sonuçlar İyileşir mi?. Ağrı Tıp Fakültesi Dergisi 2024;2(2):88 View

Books/Policy Documents

  1. Vasileiou Z, Meditskos G, Vrochidis S, Bassiliades N. Database and Expert Systems Applications - DEXA 2022 Workshops. View
  2. Xu H, Yang Z, Lan K, Yan W, Wang Z, Wang J, Zang Y, Pan J, Yan M, Zhang Z. Wireless Mobile Communication and Healthcare. View
  3. Hassan F, Rahman A, Mehmood M. Proceedings of International Conference on Information Technology and Applications. View
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