机器学习和深度学习技术在冠心病准确风险预测中的应用

Mandadi Sai Gangadhar, Kalyanam Venkata Sree Sai, Salem Hruthik Sai Kumar, Kanaparti Anil Kumar, M. Kavitha, S. S. Aravinth
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引用次数: 3

摘要

冠状动脉疾病是当今全球普遍存在的一种心脏病。这对人类来说是一个严重的问题,因为它需要适当的诊断。冠状动脉疾病的发展是由于冠状动脉中斑块的积累导致血流部分阻塞,主要由胆固醇、钙和纤维蛋白组成。冠状动脉帮助心脏将富含氧气的血液输送到全身。然而,适当的诊断和早期预测将减少发展它的可能性。这项研究探索了使用深度学习算法在早期阶段预测心脏病的可能性。这项研究的主要目的是确定一个人是否有心脏问题。通过使用深度学习技术,深度学习和各种机器学习算法都可以用于实现早期预测。数据挖掘,决策树,朴素贝叶斯,人工神经网络(ANN)是一些可以实现它的例子。本研究将采用人工神经网络模型进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning and Deep Learning Techniques on Accurate Risk Prediction of Coronary Heart Disease
Coronary artery disorder is the heart disease that is prevalent across the globe today. It's a serious issue for the humans as it requires proper diagnosis. Coronary artery disease develops over time as a result of plaque build- up in coronary arteries results in partial blockage of blood flow as the, which is primarily composed of cholesterol, calcium, and fibrin. Coronary arteries help human heart to pump oxygen-rich blood throughout the body by supplying it. However, appropriate diagnosis and early prediction will lessen the likelihood of developing it. This study explores the possibility of foreseeing cardiac illness at an early stage using deep learning algorithms. This study's primary goal is to properly determine whether a person has heart problems or not. by using deep learning techniques, Deep learning and various machine learning algorithms can both be used to implement early-stage prediction. Data mining, Decision trees, Naive Bayes, Artificial Neural Networks (ANN) are some examples through which it can be implemented. The research is going to be done using ANN Model.
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