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Evaluation of a machine learning approach utilizing wearable data for prediction of SARS-CoV-2 infection in healthcare workers
Robert P. Hirten, Lewis Tomalin, Matteo Danieletto, Eddye Golden, Micol Zweig, Sparshdeep Kaur, Drew Helmus, Anthony Biello, Renata Pyzik, Erwin P. Bottinger, Laurie Keefer, Dennis Charney, Girish N. Nadkarni, Mayte Suarez-Farinas, Zahi A. Fayad
- Artificial Intelligence and Human Health
- Hasso Plattner Institute for Digital Health at Mount Sinai
- Icahn School of Medicine at Mount Sinai
- Medicine
- Medicine - Gastroenterology
- Population Health Science and Policy
- Friedman Brain Institute
- Graduate School of Biomedical Sciences
- Investigator Track
- Professors
- Psychiatry
- Depression and Anxiety Center
- Medicine - Nephrology
- Mount Sinai Clinical Intelligence Institute
- Nephrology T32
- The Charles Bronfman Institute for Personalized Medicine
- Genetics and Genomic Sciences
- Waldman Department of Dermatology
- BioMedical Engineering and Imaging Institute
- Brain-Body Center
- CTSA ConduITS - Institutes for Translational Sciences
- Cardiovascular
- Cardiovascular Research Institute
- Center for Affective Neuroscience
- Environmental Medicine and Public Health
- Institute for Exposomic Research
- Medicine - Cardiology
- Radiology (Diagnostic, Molecular and Interventional Radiology)
Research output: Contribution to journal › Article › peer-review
5
Scopus
citations