E-Mail IMAGE: Representative specimen image of Anopheles stephensi from Mosquito Image Database. Picture shows a mosquito stored by freezing at -80C. view more Credit: Couret, J. et al. 2020 (CC-BY 2.0) Rapid and accurate identification of mosquitoes that transmit human pathogens such as malaria is an essential part of mosquito-borne disease surveillance. Now, researchers reporting in PLOS Neglected Tropical Diseases have shown the effectiveness of an artificial intelligence system--known as a Convoluted Neural Network--to classify mosquito sex, genus, species and strain. Human malaria is an ongoing public health crisis affecting multiple continents, with the highest numbers of cases and people at risk occurring in sub-Saharan Africa. However the identification of mosquitoes that transmit malaria can be difficult--some species are nearly indistinguishable even to trained taxonomists.