Medicine and Health

A method for intelligent allocation of diagnostic testing by leveraging data from commercial wearable devices: a case study on COVID-19

M. M. H. Shandhi, P. J. Cho, et al.

This study presents an innovative Intelligent Testing Allocation method to enhance the efficiency of diagnostic testing during disease outbreaks. By analyzing data from over 15,000 participants, including smartwatch metrics, the researchers revealed that resting heart rate is a more sensitive early indicator of COVID-19 than step count. The findings, attributed to the collaborative work of Md Mobashir Hasan Shandhi and colleagues, suggest that deploying ITA could significantly alleviate testing resource shortages.

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