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Diagnosis of liver disease induced by hepatitis virus using Artificial Neural Networks

机译:人工神经网络诊断肝炎病毒引起的肝病

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摘要

This paper presents an artificial neural network based approach for the diagnosis of hepatitis virus. The dataset used for this purpose is taken from the UCI machine learning database. Both supervised and unsupervised neural network models have been analyzed with different architectures, learning and activation functions. It is concluded that the supervised model performed better than the unsupervised one. The paper also compares the results of the previous studies on the diagnosis of hepatitis which use the same dataset.
机译:本文提出了一种基于人工神经网络的肝炎病毒诊断方法。用于此目的的数据集来自UCI机器学习数据库。有监督和无监督的神经网络模型都已用不同的体系结构,学习和激活功能进行了分析。结论是,监督模型的性能优于非监督模型。本文还比较了以前使用相同数据集进行肝炎诊断的研究结果。

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