VALERIA: Uma Plataforma para Auxiliar o Diagnóstico e o Monitoramento de Arboviroses

• Thomás Tabosa de Oliveira UPE
• Sebastião Rogério da Silva Neto UPE
• Igor Vitor Teixeira UPE
• Patricia Takako Endo UPE
• Vanderson Souza Sampaio FMT-HVD / FVS-AM

DOI: https://doi.org/10.5753/webmedia_estendido.2021.17623

Resumo

Arboviruses are Neglected Tropical Diseases (NTDs) that mainly affect developing countries and Brazil is one of them. Such diseases have a negative impact on quality of life of the patients. One of the main challenges in combating these diseases is the difficulty of an accurate diagnosis among the concomitant arborival diseases due the similarity of symptoms. This project proposes VALERIA, a low-cost platform based on machine learning (ML) models for assisting the diagnose of arboviruses in the national scenario. VALERIA is proposed to improve the quality of life of patients, allowing the most appropriate treatment after a diagnose and therefore presenting a great potential of generating local public policies of social impact. A prototype was already developed for diagnosis and is in validation phase by public health specialists.

Palavras-chave: valeria, virtual assistant, arbovirus, machine learning, diagnose

Referências

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Thomás Tabosa de Oliveira, Sebastião Rogério da Silva Neto, Igor Vitor Teixeira, Samuel Benjamin, Vanderson de Souza Sampaio, and Patricia Takako Endo. 2021. A comparative study of machine learning techniques for multi-class classification of arboviral diseases. Under review (2021).

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