02015nam a22001337a 4500 56148 56145 Parveen, Rahila 13MSIT27 Supervisor - Dr Akhtar Hussain Jalbani Prediction of a Malaria Using Artificial Neural Network Nawabshah: QUEST, 2016. 79P, : ABSTRACT In current era disease are very common but among all Malaria is one of the major one causes of death, where as every year, malaria is cause of about three million deaths including one-third of children .Malaria is a vector-born disease, which never transmit by it but third party that called as a vector. Female Anopheles mosquito is the vector of malaria which transmits the plasmodium into human blood cells. Several approaches have been proposed and implemented in which Malaria can only be detected by taking blood sample of patients in the laboratory. These techniques cause delay in the start of treatment. Due to which, Death ratio is considerably higher for Malaria disease in the world. The aim of this research is to speed up the process of Malaria diagnosis. An Artificial Neural Network with MPL (Multi Layer Percptron) is used along with back propagation , back propagation with momentum and resilient propagation rule for the prediction of Malaria, where as back propagation has given more accuracy than all. Among all three learning rules, Back propagation gives the more efficient results approximately 85%. In proposed approach, history and symptoms of patients are considered as an input, system analyses that data and predict the result for victim as positive or negative for Malaria. This application is useful for those areas where there is no any laboratory facility or where there is no Doctor; in such condition the person who able to operate the application by giving only verbal history and physical appearance of patient . Department Of Information Technology Engineering https://tinyurl.com/2xkt3s46 THESIS 0 0 0 0 RESEARCH RESEARCH 2016-11-28 MP/12-116 2016-11-28 THESIS 0 0 0 0 RESEARCH RESEARCH 2018-10-02 MP/27-311 2018-10-02 THESIS