A collaborative effort involving the microbiology service and research group at Vall d’Hebron University Hospital, the university Politècnica de Catalunya – BarcelonaTech (UPC), and the Probitas Foundation has unveiled a groundbreaking diagnostic method for malaria based on artificial intelligence (AI).

Malaria, an infectious disease transmitted through mosquito bites and caused by Plasmodium parasites, poses a significant global health challenge. With an estimated 249 million cases worldwide in 2022, the majority in the African region, the World Health Organization (WHO) highlights the urgent need for innovative diagnostic approaches. The current gold standard involves manual examination of blood samples under an optical microscope by an expert, leading to time-consuming and repetitive procedures with a high risk of underdiagnosis, especially in regions with limited laboratory resources.

The team’s solution, iMAGING, utilizes a mobile app employing AI to process digital images of blood samples, determining the presence, density, and stage of parasitic infection. To capture images, a cost-effective robotic microscope was created using a standard optical microscope with 3D-printed components. The mobile app connects via Bluetooth to the microscope, controlling its movements and focus for automated sample analysis. This approach significantly reduces the workload for laboratory technicians, minimizing the potential for errors.

The prototype, trained on over 2,500 images, achieved over 96% reliability in high-density samples and 94% in low-density samples, with false positives and negatives remaining below 5%. While the ultimate test lies in field performance, Dr. Joan Joseph i Munné, the project’s lead researcher from the VHIR Microbiology group, emphasizes the potential for iMAGING to address other Neglected Tropical Diseases if successful.

Supported by the World Health Organization’s initiative for digital image-based diagnosis of hemoparasites in low- and middle-income countries, the project aligns with the UPC’s Center for Cooperation in Development’s commitment to science and technology for human development. The team plans to further train the AI to enhance its capabilities, such as distinguishing between the five parasite species causing malaria, ultimately personalizing treatment for improved effectiveness.

Article written by UPC