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  • [\'Paragominas Campus, Universidade Federal Rural da Amazônia, Paragominas, Pará, Brazil.\', \'Parauapebas Campus, Universidade Federal Rural da Amazônia, Parauapebas, Pará, Brazil.\', \'Forest Engineering and Technology Department, Universidade Federal do Paraná, Curitiba, Paraná, Brazil.\', \'Forestry Engineering Department, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.\', \'Belém Campus, Universidade Federal Rural da Amazônia, Belém, Pará, Brazil.\', \'Postgraduate Program in Health Sciences, Institute of Collective Health, Universidade Federal do Oeste do Pará, Santarém, Pará, Brazil.\', \'Institute of Biological Science, Universidade Federal do Pará, Belém, Pará, Brazil.\', \'Cyberspace Institute, Universidade Federal Rural da Amazônia, Belém, Pará, Brazil.\', \'Institute of Educational Sciences, Universidade Federal do Oeste do Pará, Santarém, Pará, Brazil.\', \'Socio-Environmental Institute of Water Resources, Universidade Federal Rural da Amazônia, Belém, Pará, Brazil.\']
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  • -1
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?:doi
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  • 10.1371/journal.pone.0248161
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?:journal
  • PloS one
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?:pmid
  • 33705453
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  • 1.164
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  • 241
?:title
  • Artificial neural networks for short-term forecasting of cases, deaths, and hospital beds occupancy in the COVID-19 pandemic at the Brazilian Amazon.
?:type
?:year
  • 2021

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