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Data for the paper "App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning" This work is in progress and under review.

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Dantas_etal_PLOSOne_App-based-symptom-tracking-COVID19-

Data for the paper "App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning"

Authors: Leila F. Dantas, Igor T. Peres, Leonardo S.L. Bastos, Janaina F. Marchesi, Guilherme F.G. de Souza, João Gabriel M. Gelli, Fernanda A. Baião, Paula Maçaira, Silvio Hamacher, Fernando A. Bozza

Published at: PLoS ONE

URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0248920

DOI: https://doi.org/10.1371/journal.pone.0248920

Date: March 25th, 2021

All authors are members of the Center for Healthcare Operations and Intelligence (Núcleo de Operações e Inteligência em NOIS).

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Data for the paper "App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning" This work is in progress and under review.

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