Malaria detection using improved fuzzy algorithm

Abstract

Malaria is one of the most life-threatening diseases, which need a serious attention in today’s scenario. This disease is estimated to be having 3–6 billion infected cases worldwide annually having the mortality rate of 1–3 million people. Malaria should be diagnosed on time and treated precisely as it can lead to death of a person. The main objective of this paper is to design and describe an algorithm that can diagnose malaria in the early stage only so that a person cannot go up to the serious and hazardous stages or complications and also the mortality rate of malaria is reduced to an extent. Fuzzy logic is an approach to implement expert systems, which are portable and can diagnose malaria accurately as compared to the other systems.