Dataset for a novel AI-powered diagnostic tool for Plasmodium parasite detection authors

Abstract

Malaria remains a serious public health problem in many developing countries, particularly in Sub-Saharan Africa. Early detection and treatment of malaria are crucial in the fight against malaria in order to reduce morbidity and mortality, especially in the endemic regions. We set out to develop a simple, accurate, and efficient innovative diagnostic tool for malaria parasite identification that uses automated image processing to provide shorter diagnosis times while improving accuracy, efficiency, and standardization. Our primary goal in this study is to collect, curate, annotate and achieve blood smear images containing Plasmodium species for effective malaria diagnosis using Artificial Intelligent based system. The study curated 881 blood smear images which are categorized as positive and negative images.