The World Health Organization recommends parasite-based diagnosis before starting treatment for malaria.

A new high-tech microscope utilizing AI technology has been developed to detect malaria in returning travelers. Malaria, caused by Plasmodium parasites, results in millions of illnesses and hundreds of thousands of deaths annually.

While various diagnostic methods exist, manual light microscopy remains the standard for diagnosis. In this method, the pathologist checks out sample blood films to detect the presence, if any, of malaria parasites. However, being manual, this method is prone to errors and depends on the skills of the microscopist. High volumes of testing can also result in errors due to fatigue. (Medical Xpress)

This new microscope system combines AI detection software with an automated microscope to diagnose malaria with a clinical accuracy rate of 88%. The AI system identified malaria parasites in blood samples from returning travelers almost as effectively as human experts.

Dr. Roxanne Rees-Channer, a researcher at the Hospital for Tropical Diseases at UCLH in the UK where the study took place, stated that achieving this level of performance within a clinical context represents a significant milestone for AI algorithms focused on the disease. This indicates that the system has the potential to serve as a valuable clinical tool for diagnosis in suitable scenarios.

Despite its promising results, the system is not as accurate as expert microscopists and falsely identified some samples as positive. Nonetheless, this advancement holds potential to alleviate the burden on microscopists and improve diagnosis efficiency.

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Photo (“A close up of a mosquito on a leaf”) by Erik Karits on Unsplash