Prediction of a Malaria Using Artificial Neural Network (Record no. 56148)

MARC details
000 -LEADER
fixed length control field 02015nam a22001337a 4500
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Parveen, Rahila
-- 13MSIT27
-- Supervisor - Dr Akhtar Hussain Jalbani
245 ## - TITLE STATEMENT
Title Prediction of a Malaria Using Artificial Neural Network
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Nawabshah:
Name of publisher QUEST,
Year of publication 2016.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 79P, :
500 ## - GENERAL NOTE
General note <br/>ABSTRACT<br/><br/>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.<br/><br/>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%.<br/><br/>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<br/><br/> . <br/><br/><br/> <br/><br/>
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Department Of Information Technology Engineering
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://tinyurl.com/2xkt3s46
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Thesis and Dissertation
Holdings
Withdrawn status Lost status Home library Current library Date acquired Accession Number Koha item type
    Research Section Research Section 28/11/2016 MP/12-116 Thesis and Dissertation
    Research Section Research Section 02/10/2018 MP/27-311 Thesis and Dissertation