Malaria is an infectious disease transmitted by mosquito bites and caused by parasites of the genus Plasmodium. The World Health Organisation estimates that by 2022 there were 249 million cases worldwide, 93% of which were in African regions, which also accounted for 95% of deaths. The same report also warned that climate change and globalisation are  spreading the mosquito to new areas that have little capacity  or resources to deal with it. Aside from the problems caused by the disease, the current method of diagnosis is by expert visualisation of parasites from blood samples under an optical microscope. This is a manual, time-consuming and repetitive procedure, which, coupled with a lack of laboratory technicians and instruments, leads to a large under-diagnosis. Until now, any step to automate the process increased exponentially its cost, which complicated its implementation in countries with few health resources.

In our commitment to improve the health of the most vulnerable people, we have promoted the iMAGING project with a multidisciplinary team formed by the Microbiology Service of the Hospital Vall d’Hebron, the Microbiology Research Group of the Vall d’Hebron Institut de Recerca (VHIR), the Universitat Politècnica de Catalunya - Barcelona Tech (UPC) and Probitas.

The new diagnostic method for malaria is an artificial intelligence-based system that combines a mobile application with a low-cost robotic microscope. The design is intended to be a useful and effective method in countries with limited health resources, where the disease is endemic.

The pilot test has been developed in the Microbiology laboratory of the Vall d'Hebron Drassanes International Health Centre and with the research groups in Computational Biology and Complex Systems (BIOCOM-UPC), Image and Video Processing (GPI) and Database Technologies and Information Management (DTMI) of the UPC.

The description of the first iMAGING prototype has been published in the scientific journal Frontiers in Microbiology. The system has demonstrated a reliability of more than 90%. The next step will be the evaluation of pilot tests in the Drassanes laboratory and in the field.

An automatic microscope controlled by Bluetooth

iMAGING is a mobile app that uses artificial intelligence to process digital images of blood samples to determine whether infection is present or not. If positive, it also determines the density and stage of the parasitic infection. To capture the images, a robotic microscope has been created from an optical microscope with parts created using 3D printing, which reduces its cost.

The app connects via Bluetooth to the microscope and controls the microscope's movements and focus to automatically analyse the sample and obtain the images needed for diagnosis. The technical staff must only prepare the samples, which greatly reduces their workload and the possibility of errors.

The prototype has been trained on more than 2,500 images and has achieved a reliability of more than 96% for high-density samples and 94% for low-density samples. The promoters have agreed that "if successful, it can open the door to adapting it to Neglected Tropical Diseases".

The next goal is to further train artificial intelligence to introduce improvements such as differentiating between the five different species of parasites that cause the disease. This will allow much more personalised treatments, improving effectiveness. The system is supported by the World Health Organisation as part of its initiative for digital imaging diagnosis of haemoparasites in low- and middle-income countries.