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Malaria Outbreak Prediction using Machine Learning


Akash Chandra Patel , Noida International University; Manish Mishra, Noida International University; Sunil Chaurasiya, Noida International University; Anash Shameem, Noida International University; Abhishek Saxena, Noida International University


Malaria, Support Vector Machine, Outbreak, Machine Learning, Public Health, Artificial Neural Network


There are various diseases whose early detection can prevent the patient from tired and cumbersome medical treatment. Malaria is one of the widely spreading diseases in India [1]. It is early prediction and control is a major challenge for medical science. Various international health community and health based organizations working for its eradication are in greatest need for its prevention. In this paper, we proposed the Malaria Outbreak Prediction Model using Machine Learning which can help us as an outbreak prediction tool to identify potential outbreaks of Malaria. In this study, two popular machine learning classification algorithms Support Vector Machine (SVM) and Artificial Neural Network (ANN) are used for Malaria prediction using a dataset of some cities.

Other Details

Paper ID: IJSRDV7I20964
Published in: Volume : 7, Issue : 2
Publication Date: 01/05/2019
Page(s): 1067-1069

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