CoviText: Search Engine of the Medical Literature about COVID-19

Authors

  • Jedson Gabriel Ferreira de Paula Universidade Estadual do Oeste do Paraná
  • Rômulo César Silva Universidade Estadual do Oeste do Paraná

DOI:

https://doi.org/10.59681/2175-4411.v15.iEspecial.2023.1075

Keywords:

COVID-19, Machine Learning, Data Mining

Abstract

In the first months of 2020, the COVID-19 pandemic has severely affected several countries, including Brazil. Due to the possibility of collapse in health systems and economic losses, there is an increasing number of related researches, generating a large volume of scholarly articles, such as the CORD-19 dataset (87.5 GB, base year: 2022), available at the Kaggle website. Due to the rapid acceleration in new coronavirus literature, making it difficult for the medical research community to keep up, it is necessary to find ways of browsing and consulting what is already known about the Sars-Cov-2 virus and its related disease. In order to facilitate this process, this work presents the CoviText tool: a search engine for the medical literature on COVID-19, developed using text mining and machine learning techniques.

Author Biographies

Jedson Gabriel Ferreira de Paula, Universidade Estadual do Oeste do Paraná

Discente de Ciência da Computação na Universidade Estadual do Oeste do Paraná - Campus de Foz do Iguaçu.

Rômulo César Silva, Universidade Estadual do Oeste do Paraná

Professor adjunto de Ciência da Computação na Universidade Estadual do Oeste do Paraná - Campus de Foz do Iguaçu.

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Published

2023-07-20

How to Cite

Paula, J. G. F. de, & Silva, R. C. (2023). CoviText: Search Engine of the Medical Literature about COVID-19. Journal of Health Informatics, 15(Especial). https://doi.org/10.59681/2175-4411.v15.iEspecial.2023.1075

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