Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review.

ABSTRACT: Malaria is an infectious disease caused by parasites of the genus Plasmodium spp. It is transmitted to humans by the bite of an infected female Anopheles mosquito. It is the most common disease in resource-poor settings, with 241 million malaria cases reported in 2020 according to the World Health Organization. Optical microscopy examination of blood smears is the gold standard technique for malaria diagnosis; however, it is a time-consuming method and a well-trained microscopist is needed to perform the microbiological diagnosis. New techniques based on digital imaging analysis by deep learning and artificial intelligence methods are a challenging alternative tool for the diagnosis of infectious diseases. In particular, systems based on Convolutional Neural Networks for imag

SUBMITTER: Maturana CR 

PROVIDER: S-EPMC9705958 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature