Detection of Visceral Leishmaniasis in Humans Using Neural Networks

• Viviane Barbosa Leal Dias UFPI
• Armando Luz Borges UFPI
• Clésio de Araujo Gonçalves UFPI / IFSertão
• Ana Carolina Landim Pacheco UFPI
• Romuere Rodrigues Veloso e Silva UFPI

DOI: https://doi.org/10.5753/enucompi.2023.26623

Abstract

Leishmaniasis is a serious disease transmitted by infected mosquitoes, which can be fatal without adequate treatment. A quick and efficient diagnosis is essential. Although Computer Vision techniques can help with diagnosis, they are often expensive and time-consuming due to high computational requirements. This study aims to train low computational cost convolutional neural networks to assist in the diagnosis of Visceral Leishmaniasis. Our results were compared with four previous works, and our method showed significant and promising results. This demonstrates that low-cost convolutional neural networks can be an effective approach for the automated diagnosis of visceral leishmaniasis in humans.

Keywords: Deep Learning, Computer Vision, Visceral Leishmaniasis

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