Evaluation of Machine Learning to Detect Influenza Using Wearable Sensor Data and Patient-Reported Symptoms: A Cohort Study (Preprint)-Reference-Cited by-同舟云学术

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Evaluation of Machine Learning to Detect Influenza Using Wearable Sensor Data and Patient-Reported Symptoms: A Cohort Study (Preprint)

Published:2023-04-05 Issue: Volume: Page:
ISSN:1438-8871
Container-title:Journal of Medical Internet Research
language:en
Short-container-title:

Author:

Farooq Kamran^ORCID,Lim Melody^ORCID,Dennison-Hall Lawrence^ORCID,Janson Finn^ORCID,Olszewska Aspen Hazel^ORCID,Ahmad Zabidi Muhammad Mamduh^ORCID,Haratym-Rojek Anna^ORCID,Narowski Karol^ORCID,Clinch Barry^ORCID,Prunotto Marco^ORCID,Chawla Devika^ORCID,Hunter Victoria^ORCID,Ukachukwu Vincent^ORCID

Publisher

JMIR Publications Inc.

Reference28 articles.

1. Prediction of viral symptoms using wearable technology and artificial intelligence: A pilot study in healthcare workers

2. Passive detection of COVID-19 with wearable sensors and explainable machine learning algorithms

3. Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset

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

5. A Neutralizing Monoclonal Antibody for Hospitalized Patients with Covid-19

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