A deep learning approach in detection of malaria and acute lymphoblastic leukemia diseases utilising blood smear microscopic images

Abstract

The numerous rising infections and deaths of malaria and acute lymphoblastic leukaemia (ALL) highlights the urgent need for early, useful, and efficient diagnosis methods. Recently, the framework of artificial intelligence has been applied to minimize time-consuming tasks, to increase the accuracy and flexibility of clinical diagnoses, and to reduce the pressure on physicians, diagnosticians, and clinical experts...