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Prediction of Hepatitis Disease Using Machine Learning Technique

Authors :
Gowtham Kishore Indukuri
Vedha Krishna Yarasuri
Aswathy K Nair
Source :
2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC).
Publication Year :
2019
Publisher :
IEEE, 2019.

Abstract

The objective of this work is to choose the best tool for diagnosis and detection of Hepatitis as well as for the prediction of life expectancy of Hepatitis patients. In this work, a comparative study between various machine learning tools and neural networks were carried out. The performance metric is based on the accuracy rate and the mean square error. The Machine Learning (ML) algorithms such as Support Vector Machines (SVM), K Nearest Neighbor (KNN) and Artificial Neural Network (ANN) were considered as the classification and prediction tools for diagnosing Hepatitis disease. A brief study on the above algorithms were performed based on the prediction accuracy of disease diagnosis. All the ML algorithms were implemented and validated using MATLAB software.

Details

Database :
OpenAIRE
Journal :
2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)
Accession number :
edsair.doi...........dc95e63dc136102c9fedfe2e3bfa1921
Full Text :
https://doi.org/10.1109/i-smac47947.2019.9032585