Frailty Identification Using Heart Rate Dynamics: A Deep Learning Approach-Reference-Cited by-同舟云学术

Frailty Identification Using Heart Rate Dynamics: A Deep Learning Approach

Published:2022-07 Issue:7 Volume:26 Page:3409-3417
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Eskandari Maryam¹^ORCID,Parvaneh Saman²^ORCID,Ehsani Hossein³,Fain Mindy⁴,Toosizadeh Nima⁵^ORCID

Affiliation:

1. Department of Computer Sciences, University of Arizona, Tucson, AZ, USA

2. Edwards Life Sciences, Irvine, CA, USA

3. Kinesiology Department, University of Maryland, College Park, MD, USA

4. Division of Geriatrics General Internal Medicine and Palliative Medicine Department of Medicine, University of Arizona, Tucson, AZ, USA

5. Department of Biomedical Engineering and the Division of Geriatrics General Internal Medicine and Palliative Medicine Department of Medicine, University of Arizona, Tucson, AZ, USA

Funder

Institute of Aging

NIA/NIH

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/ielx7/6221020/9813470/09720199.pdf?arnumber=9720199

Reference46 articles.

1. Neural networks versus Logistic regression for 30 days all-cause readmission prediction

2. Heart Rate Recovery and Treadmill Exercise Score as Predictors of Mortality in Patients Referred for Exercise ECG

3. Deep learning approach for ECG-based automatic sleep state classification in preterm infants

4. Identification of Frailty in Chronic Heart Failure

5. Improving a Measure of Mobility-Related Fatigue (The Mobility-Tiredness Scale) by Establishing Item Intensity

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