Data-Driven Guided Attention for Analysis of Physiological Waveforms With Deep Learning-Reference-Cited by-同舟云学术

Data-Driven Guided Attention for Analysis of Physiological Waveforms With Deep Learning

Published:2022-11 Issue:11 Volume:26 Page:5482-5493
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Martinez Jonathan¹^ORCID,Nowroozilarki Zhale¹,Jafari Roozbeh²^ORCID,Mortazavi Bobak J.¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA

2. Department of Biomedical Engineering, Electrical and Computer Engineering, Computer Science and Engineering, Texas A&M University, College Station, TX, USA

Funder

National Institute of Health

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/9945616/09858630.pdf?arnumber=9858630

Reference49 articles.

1. Long-term blood pressure prediction with deep recurrent neural networks

2. A Novel Continuous Blood Pressure Estimation Approach Based on Data Mining Techniques

3. Split ‘n’ merge net: A dynamic masking network for multi-task attention

4. An Unobtrusive and Calibration-free Blood Pressure Estimation Method using Photoplethysmography and Biometrics

5. A multistage deep neural network model for blood pressure estimation using photoplethysmogram signals

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