Published on in Vol 22, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://www.medrxiv.org/content/10.1101/2020.09.18.20197582v1, first published .
Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Journals

  1. Gangloff C, Rafi S, Bouzillé G, Soulat L, Cuggia M. Machine learning is the key to diagnose COVID-19: a proof-of-concept study. Scientific Reports 2021;11(1) View
  2. Guo Y, Zhang Y, Lyu T, Prosperi M, Wang F, Xu H, Bian J. The application of artificial intelligence and data integration in COVID-19 studies: a scoping review. Journal of the American Medical Informatics Association 2021;28(9):2050 View
  3. Tolmachev I, Kaverina I, Vrazhnov D, Starikov I, Starikova E, Kostuchenko E. Application of Artificial Intelligence Methods Depending on the Tasks Solved during COVID-19 Pandemic. COVID 2022;2(10):1341 View
  4. Nakano-Baker O, Fong H, Shukla S, Lee R, Cai L, Godin D, Hennig T, Rath S, Novosselov I, Dogan S, Sarikaya M, MacKenzie J. Data-driven design of a multiplexed, peptide-sensitized transistor to detect breath VOC markers of COVID-19. Biosensors and Bioelectronics 2023;229:115237 View

Books/Policy Documents

  1. Nayak S, Ganguly C, Gupta A. Artificial Intelligence and Machine Learning Methods in COVID-19 and Related Health Diseases. View