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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

Crossref DOI link: https://doi.org/10.1186/s13049-020-00808-8

Published Online: 2020-12-01

Published Print: 2020-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Langer, Thomas https://orcid.org/0000-0002-9725-8520
Favarato, Martina

Giudici, Riccardo

Bassi, Gabriele

Garberi, Roberta

Villa, Fabiana

Gay, Hedwige

Zeduri, Anna

Bragagnolo, Sara

Molteni, Alberto

Beretta, Andrea

Corradin, Matteo

Moreno, Mauro

Vismara, Chiara

Perno, Carlo Federico

Buscema, Massimo

Grossi, Enzo

Fumagalli, Roberto
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Text and Data Mining valid from 2020-12-01

Version of Record valid from 2020-12-01
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Article History

Received: 26 June 2020

Accepted: 6 November 2020

First Online: 1 December 2020

Ethics approval and consent to participate

: This study was approved by the Institutional Review Board of our hospital (N°3733). The need for informed consent from individual patients was waived owing to the retrospective nature of the study and considering the complete data anonymization.

: This study was approved by the Institutional Review Board of our hospital (N°3733). The need for informed consent from individual patients was waived owing to the retrospective nature of the study and considering the complete data anonymization.

: The authors declare that they have no competing interests relevant to the manuscript.

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