ePoster on Malaria Microscopy with Artificial Intelligence on ECCMID 2021

Thin and thick film evaluations are the gold standard of malaria diagnostic tests. However, a correct diagnosis requires a lengthy evaluation at the microscope by well-trained experts. Artificial intelligence is now used in various application areas to support human decision-making processes. MetaSystems, in collaboration with the University of Milano and the Ospedale Fatebenefratelli-Sacco, Milano, has developed a deep learning algorithm for Metafer to improve the sensitivity and specificity of malaria microscopy-based evaluations. The resulting Deep Neural Network (DNN) was able to achieve similar classification values in the identification of throphozoites of the pathogen P. falciparum as in manual evaluation. The results of this development has been presented as an ePoster at ECCMID 2021 under the title 'Deep learning and microscopy: new perspectives in malaria diagnosis' (Poster No. 1235).

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