Indonesia is developing an AI model to improve malaria diagnosis and support its 2030 elimination target. Trained on over 1,300 blood sample images, the model identifies four parasite species with 80.6% accuracy. It enhances early detection despite challenges from parasite shape changes during their lifecycle.
Indonesia is building an artificial intelligence model to enhance malaria diagnosis as part of its national plan to eliminate the disease by 2030. This model aims to accelerate detection and improve healthcare access in regions where malaria remains widespread.
The system has been trained using over 1,300 microscopic images of blood samples containing malaria parasites. It can identify four species of parasites with 80.6% accuracy, recognize infected red blood cells, analyze their shape and size, and classify the growth stage of the parasites.
One major challenge in development is the parasite’s changing morphology throughout its lifecycle. With nearly 500K malaria cases recorded in 2024—mostly in a specific region—this AI innovation is expected to strengthen early detection and support national eradication efforts.