VALERIA: um aplicativo para auxiliar no diagnóstico diferencial de arboviroses

  • Sebastião Rogerio da Silva Neto UPE
  • Thomás Tabosa de Oliveira UPE
  • Igor Vitor Teixeira UPE
  • Élisson da Silva Rocha UPE
  • Kayo Henrique de Carvalho Monteiro UPE
  • Vanderson de Souza Sampaio ITpS
  • Patricia Takako Endo UPE

Resumo


Brazil is one of the countries with the highest incidence of Neglected Tropical Diseases (NTDs), especially in the North and Northwest regions. Arboviruses, such as Dengue and Chikungunya, transmitted by mosquitoes, are the most common in the country. Arbovirus infection can cause persistent symptoms and negatively impact patients’ quality of life, resulting in economic challenges for public health. Accurate diagnoses are essential, but the financial limitation for large-scale laboratory testing is a barrier. In this context, VALERIA is presented as a solution through the use of machine learning models to assist in the classification of arboviruses, relying solely on patients’ clinical information, offering targeted treatments, and promoting positive social impact in the Brazilian territory.

Palavras-chave: Neglected Tropical Diseases, Quality of life, Clinical information, Machine learning

Referências

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Publicado
23/10/2023
NETO, Sebastião Rogerio da Silva; DE OLIVEIRA, Thomás Tabosa; TEIXEIRA, Igor Vitor; ROCHA, Élisson da Silva; MONTEIRO, Kayo Henrique de Carvalho; SAMPAIO, Vanderson de Souza; ENDO, Patricia Takako. VALERIA: um aplicativo para auxiliar no diagnóstico diferencial de arboviroses. In: WORKSHOP DE FERRAMENTAS E APLICAÇÕES - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 29. , 2023, Ribeirão Preto/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 115-118. ISSN 2596-1683. DOI: https://doi.org/10.5753/webmedia_estendido.2023.235561.