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A Web Based Framework for Liver Disease Diagnosis using Combined Machine Learning Models

机译:使用组合机器学习模型的基于Web的肝病诊断框架

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The liver is one of the most vital organs of the human body. Liver disease is any condition that harms the liver and inhibits its regular functioning. The risk presented by liver diseases is substantial, and unless it’s diagnosed at an early stage, organ failure is inevitable. However, since the liver functions normally even when partially damaged, problems with patients are not discovered easily. This paper aims to present a faster solution where liver disorders can be recognised earlier by analysing the levels of enzymes in the blood. The web-based framework presented in this paper aids doctors in making quicker and more accurate diagnoses by using three optimized machine learning algorithms - weighted K-Nearest Neighbours, Decision Trees, Artificial Neural Networks- to classify the given data and produce results.
机译:肝脏是人体最重要的器官之一。肝病是任何损害肝脏并抑制其正常功能的疾病。肝病带来的风险是巨大的,除非早诊断出,否则器官衰竭是不可避免的。但是,由于即使部分受损,肝脏也能正常发挥功能,因此不易发现患者的问题。本文旨在提供一种更快的解决方案,通过分析血液中酶的水平,可以更早地识别出肝脏疾病。本文介绍的基于Web的框架通过使用三种优化的机器学习算法-加权K最近邻,决策树,人工神经网络-对给定数据进行分类并产生结果,从而帮助医生更快,更准确地进行诊断。

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