Connection

Co-Authors

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This is a "connection" page, showing publications co-authored by Zahi Fayad and Matteo Danieletto.
Zahi Fayad
Connection Strength
0.589
Matteo Danieletto
  1. Factors Associated With Longitudinal Psychological and Physiological Stress in Health Care Workers During the COVID-19 Pandemic: Observational Study Using Apple Watch Data. J Med Internet Res. 2021 09 13; 23(9):e31295.
    View in: PubMed
    Score: 0.242
  2. Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study. J Med Internet Res. 2021 02 22; 23(2):e26107.
    View in: PubMed
    Score: 0.233
  3. Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City. BMJ Open. 2020 11 27; 10(11):e040736.
    View in: PubMed
    Score: 0.057
  4. Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation. J Med Internet Res. 2020 11 06; 22(11):e24018.
    View in: PubMed
    Score: 0.057
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.