Applying FOSS Support Vector Machine and Rough Sets on COVID-19 Cases Triage

  • Vinícius Hansen UDESC
  • Kalyl Henings UDESC
  • Gilmário Barbosa dos Santos UDESC

Resumo


Free and Open Source Software (FOSS) is attractive for various reasons, calling the attention of developers of systems applied on the field of primary health systems, specially in third world countries. Considering the recent COVID-19 pandemic, FOSS approach has an important role to play on the development of systems on epidemiological surveillance and triage of cases according to the level of priority and taking in account the uncertainty in diagnosis. This paper formulated a model using Support Vector Machine and Rough Sets that demonstrates a proficiency in discerning between COVID, Uncertain, and Normal cases for the triage of cases based on chest X-rays. The results depicts an accuracy of 91.82%.

Palavras-chave: FOSS, Rough Sets, Support Vector Machine, Machine Learning, COVID-19, Uncertainty

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Publicado
18/10/2023
HANSEN, Vinícius; HENINGS, Kalyl; SANTOS, Gilmário Barbosa dos. Applying FOSS Support Vector Machine and Rough Sets on COVID-19 Cases Triage. In: CONGRESSO LATINO-AMERICANO DE SOFTWARE LIVRE E TECNOLOGIAS ABERTAS (LATINOWARE), 20. , 2023, Foz do Iguaçu/PR. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 22-27. DOI: https://doi.org/10.5753/latinoware.2023.236290.