Deep Learning applications for disease diagnosis and identification of insect vectors
Aplicaciones del deep learning en salud
Keywords:
Deep Learning. Diagnosis. Leishmaniasis. Chagas Disease.Abstract
Deep learning is a machine learning technique in which the computational algorithm learns patterns directly from images previously classified. The present essay aims to show some applications for clinical diagnosis and identification of insect vectors to encourage health professionals to use the tool to perform automated analyzes. Deep learning has been applied to the diagnosis of cancer, cardiac fibrosis, tuberculosis, detection of parasites such as Plasmodium and Leishmania, and to identify insect vectors. At the University of Brasília, deep learning has been used to develop a tool to identify ulcers caused by leishmaniasis as well as to detect Leishmania parasites. Moreover, deep learning was applied to identify species of vectors of Chagas disease, an important contribution to the epidemiological survaillance of the disease. The use of deep learning involves some ethical and procedural issues that are discussed. Finally, the essay points out perspectives of app development that assist health professionals in the diagnosis of Leishmaniasis and Chagas' disease vectors, which meets the goals of translational research.
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