figshare
Browse

Additional file 1 of Development of machine learning models to predict RT-PCR results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients with influenza-like symptoms using only basic clinical data

Download (1.08 MB)
journal contribution
posted on 2020-12-02, 04:56 authored by Thomas Langer, Martina Favarato, Riccardo Giudici, Gabriele Bassi, Roberta Garberi, Fabiana Villa, Hedwige Gay, Anna Zeduri, Sara Bragagnolo, Alberto Molteni, Andrea Beretta, Matteo Corradin, Mauro Moreno, Chiara Vismara, Carlo Federico Perno, Massimo Buscema, Enzo Grossi, Roberto Fumagalli
Additional file 1. Additional materials, methods and results.

History

Related Materials

  1. 1.
    DOI - References https://doi.org/10.1001/jama.2020.5394
  2. 2.
    DOI - References https://doi.org/10.1001/jamainternmed.2020.3539
  3. 3.
    DOI - References https://doi.org/10.1056/NEJMoa2001017
  4. 4.
    DOI - References https://doi.org/10.1056/NEJMoa2001316
  5. 5.
    DOI - References https://doi.org/10.1093/cid/ciaa310
  6. 6.
    DOI - References https://doi.org/10.1515/cclm-2020-0285
  7. 7.
    DOI - References https://doi.org/10.1016/S0140-6736(20)30211-7
  8. 8.
    DOI - References https://doi.org/10.1056/NEJMoa030747
  9. 9.
    DOI - References https://doi.org/10.1038/s41579-018-0118-9
  10. 10.
    DOI - References https://doi.org/10.1038/s41591-020-0931-3

Usage metrics

    Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine

    Categories

    Keywords

    Severe acute respiratory syndrome coronavirus 2Emergency service, hospitalPandemicsCritical careArtificial intelligenceSupervised machine learning

    Licence

    CC BY + CC0

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC