Mobile microscopy and telemedicine platform assisted by deep learning for the quantification of Trichuris trichiura infection - Dacal, Elena; Bermejo-Peláez, David; Lin, Lin; Álamo, Elisa; Cuadrado, Daniel; Martínez, Álvaro; Mousa, Adriana; Postigo, María; Soto, Alicia; Sukosd, Endre; Vladimirov, Alexander; Mwandawiro, Charles; et al. (PLOS Neglected Tropical Diseases, 2021)
Author summary Soil-transmitted helminths (STH), including hookworm, Ascaris lumbricoides and Trichuris trichiura, are common intestinal infections in low-income countries. Global estimates indicate that more than 1.5 billion people are infected with at least one STH species. They cause anaemia, gastro-intestinal problems, tiredness amongst other symptoms. Diagnosis of STH infection is mainly performed by analyzing stool samples under the microscope using the so-called Kato-Katz technique. However, the analysis of Kato-Katz samples, which is usually performed by microscopy experts, is a subjective procedure based on visual inspection of the samples and requires to be done in a short period of time since the sample preparation. In this work we proposed a novel system to digitize the microscopy samples using an affordable 3D-printed adapter and smartphones. Digitized images were uploaded to a telemedicine platform enabling remote diagnosis. Additionally, the digitized images were automatically analyzed by an Artificial Intelligence (AI) algorithm which was fully-integrated in the telemedicine platform, performing an automatic and objective count of different types of STH parasites (A. lumbricoides and T. trichiura).