When Brazilian immunologist Helder Nakaya visited Evandro Chagas Institute in Belém (the capital of Pará state, Brazil) in 2017, there was a commotion because one of its best microscopists was retiring and much of the knowledge used for fast and accurate identification of the protozoan Leishmania would be lost."I was dismayed by the waste of losing all that expertise, which it had taken decades to acquire. We began researching and trying to train a computer program to use this professional's knowledge to identify microorganisms cheaply," Nakaya told Agência FAPESP.
Five years later, a group of researchers led by Nakaya and scientist Mauro César Cafundó de Morais published the findings of a study showing that artificial intelligence can be used to detect Trypanosoma cruzi, the parasite that causes Chagas disease, in images of blood samples taken with a smartphone camera and analyzed by optical microscope.The algorithm developed by the group is available from an article in the scientific journal PeerJ. The research was supported by FAPESP (projects 20/12017-9, and 15/22308-2), and involved professionals in a range of fields from biology to mathematics and computing.
"We got good results in this machine learning initiative. The algorithm works well for Chagas and can be adapted for other purposes that depend on images, such as analyzing samples of feces, skin and colposcopies," said Nakaya, a principal investigator at the Center for Research on Inflammatory Diseases (CRID), a Research, Innovation and Dissemination Center (RIDC) funded by FAPESP and hosted by the University of São Paulo's Ribeirão Preto Medical School (FMRP-USP). Nakaya is also a researcher at Albert Einstein Jewish Hospital (HIAE), Scientific Platform Pasteur-USP (SPPU), and Instituto Todos pela Saúde (ITpS).
One of the techniques used to diagnose Chagas is performed by microscopists trained to detect the parasite in blood samples. This requires a professional microscope, which can be coupled to a high-resolution camera, but the method tends to be too expensive and unaffordable for low-income patients.Classified by the World Health…