Classification of Patient Recovery From COVID-19 Symptoms Using Consumer Wearables and Machine Learning-Reference-Cited by-同舟云学术

Classification of Patient Recovery From COVID-19 Symptoms Using Consumer Wearables and Machine Learning

Published:2023-03 Issue:3 Volume:27 Page:1271-1282
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Leitner Jared¹^ORCID,Behnke Alexander¹,Chiang Po-Han¹^ORCID,Ritter Michele²,Millen Marlene²,Dey Sujit³

Affiliation:

1. Electrical and Computer Engineering Department, University of California San Diego, La Jolla, CA, USA

2. UCSD Health, San Diego, CA, USA

3. Electrical and Computer Engineering Department and Head of the Mobile Systems Design Laboratory, University of California San Diego, La Jolla, CA, USA

Funder

UC San Diego Center for Wireless Communications

Connected Health Program

Jacobs Family Endowed Chair Fund

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/ielx7/6221020/10063192/10025371.pdf?arnumber=10025371

Reference50 articles.

1. Real-time alerting system for COVID-19 and other stress events using wearable data

2. Pre-symptomatic detection of COVID-19 from smartwatch data

3. Assessment of physiological signs associated with COVID-19 measured using wearable devices

4. Wearable sensor data and self-reported symptoms for COVID-19 detection

5. Machine learning-based prediction of COVID-19 diagnosis based on symptoms

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