A comparative study on the efficiency of machine learning techniques for recognizing malaria symptoms using microscopically image data
P. Sravanthi, Mittapally Kumara Swamy, Jonnadula Narasimharao, Indur Ranaveer · 2025
A key ingredient of malaria, a blood-borne disease spread by mosquitoes, are parasites called Plasmodium. Creating a blood smear and using a microscope to examine the blood-stained spread so as to recognize the pathogen genus Plasmodium is the traditional method of diagnosing malaria. This strategy heavily relies on the expertise of licensed professionals. In this study, the usual method—which has significant issues with sensitivity and sympathy—is replaced with straightforward machine learning algorithms to distinguish the parasite from blood smears to identify malaria? Without the need for experts or blood staining, the proposed technology leverages patient pictures to identify the occurrence of malaria.