Prediction of Hepatitis Disease Using Machine Learning Technique

Vedha Krishna Yarasuri, Gowtham Kishore Indukuri, Aswathy K. Nair
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引用次数: 19

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.
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利用机器学习技术预测肝炎疾病
这项工作的目的是为肝炎的诊断和检测以及预测肝炎患者的预期寿命选择最好的工具。在这项工作中,对各种机器学习工具和神经网络进行了比较研究。性能指标是基于准确率和均方误差。将支持向量机(SVM)、K近邻(KNN)和人工神经网络(ANN)等机器学习(ML)算法作为肝炎疾病诊断的分类和预测工具。基于疾病诊断的预测精度,对上述算法进行了简要的研究。利用MATLAB软件对所有ML算法进行了实现和验证。
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