利用机器学习分类器有效预测心脏病

B. Venkataramanaiah, Sasikar A., V. P. Naveen Kumar Reddy, V. L. Prasanna Kumar
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引用次数: 0

摘要

在这个技术不断升级的世界里,心脏病学领域开发了许多类型的软件设备,帮助患者得到更好的治疗。随着人工智能技术的不断创新,对心脏疾病检测的需求不断增加。主要的机器学习技术用于识别心血管疾病。我们制定了一个有效而准确的框架来发现冠状动脉疾病,这个框架依赖于人工智能程序。这包含了一些AI模型来给出精确的安排,而不是只有一个模型。朴素贝叶斯,已知,随机森林和决策树用于分析和测试心血管疾病。高光选择计算用于高光选择,提高了排序的准确性,缩短了排序框架的执行周期。该框架在python阶段通过利用AI执行和准备
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Prediction of Heart Diseases by using Machine Learning Classifiers
In this world of upgrading technologies many types of software equipment are developed in the cardiology sector which help patients to get better treatment. With the present innovative techniques in Artificial intelligence the demand increases in detecting heart diseases. The main machine learning techniques are used for identifying cardiovascular diseases. We made a productive and exact framework to finding coronary illness and the framework depends on AI procedures. This contains a few AI models to give exact arrangements rather than having just one model. Naive Bayes, knn, Random Forest and Decision Tree are used for analysis and testing cardiovascular diseases. The highlights choice calculations utilized for high light choice to build the order exactness and lessen the execution season of arrangement framework. The framework was executed and prepared in the python stage by utilizing the AI
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