CovIdentify Dataset
收藏DataCite Commons2024-11-25 更新2025-04-16 收录
下载链接：
https://physionet.org/content/covidentify/1.0.0/
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资源简介：
This dataset supports the study "A method for intelligent allocation of
diagnostic testing by leveraging data from commercial wearable devices: a case
study on COVID-19," which developed an Intelligent Testing Allocation (ITA)
method. The study demonstrated the efficacy of using continuous digital
biomarkers like resting heart rate and steps to enhance COVID-19 diagnostic
testing positivity rates. The findings suggest significant potential for
large-scale, symptom-independent surveillance testing to alleviate diagnostic
test shortages. The provided data is from the CovIdentify study launched by
Duke's BIG IDEAs Lab in the Biomedical Engineering Department. From April 2nd,
2020 to May 25th, 2021, 2,887 participants connected their smartwatches to the
CovIdentify platform, including 1,689 Garmin, 1,091 Fitbit, and 107 Apple
smartwatches
提供机构：
PhysioNet
创建时间：
2024-11-12
