A Comparative Study on Machine Learning and Artificial Neural Networking Algorithms

Udaiyakumar Ramamoorthy, N. Vijayalakshmi, M. Prashanthram, S. Jayaprakash
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引用次数: 1

Abstract

The diagnosis of heart disease by classical medical approach takes huge amount of time. Besides blood tests and X-ray this approach includes multiple tests like MRI, Echocardiogram and whose results are prone to misdiagnosis. Our proposed model can predict whether a patient with given health parameters and certain test results is affected by a heart disease. The proposed model uses AI approach with several ML algorithms like KNN, SVM, Decision Tree, Random forest classifiers and also with deep neural networks. This prediction is done based on the historical data collected from different medical Institutes in Central Europe.
机器学习与人工神经网络算法的比较研究
传统医学方法对心脏病的诊断需要耗费大量的时间。除了血液检查和x光检查外,这种方法还包括MRI、超声心动图等多种检查,其结果容易误诊。我们提出的模型可以预测给定健康参数和某些测试结果的患者是否受到心脏病的影响。提出的模型使用人工智能方法与几种ML算法,如KNN, SVM,决策树,随机森林分类器和深度神经网络。这一预测是根据中欧不同医疗机构收集的历史数据做出的。
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