Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26107, first published .
Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study

Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study

Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study

Journals

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  38. Hirten R, Tomalin L, Danieletto M, Golden E, Zweig M, Kaur S, Helmus D, Biello A, Pyzik R, Bottinger E, Keefer L, Charney D, Nadkarni G, Suarez-Farinas M, Fayad Z. Evaluation of a machine learning approach utilizing wearable data for prediction of SARS-CoV-2 infection in healthcare workers. JAMIA Open 2022;5(2) View
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Books/Policy Documents

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