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Machine Learning Techniques for Heart Disease Prediction: A Comparative Study and Analysis

机译:心脏病预测机器学习技术:比较研究与分析

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摘要

Nowadays, people are getting caught in their day-to-day lives doing their work and other things and ignoring their health. Due to this hectic life and ignorance towards their health, the number of people getting sick increases every day. Moreover, most of the people are suffering from a disease like heart disease. Global deaths of almost 31% population are due to heart-related disease as data contributed by the World Health Organization (WHO). So, the prediction of happening heart disease or not becomes important for the medical field. However, data received by the medical sector or hospitals is so huge that sometimes it becomes difficult to analyze. Using machine learning techniques for this prediction and handling of data can become very efficient for medical people. Hence in this study, we have discussed the heart disease and its risk factors and explained machine learning techniques. Using that machine learning techniques, we have predicted heart disease and provided a comparative analysis of the algorithms for machine learning used for the experiment of the prediction. The goal or objective of this research is completely related to the prediction of heart disease via a machine learning technique and analysis of them.
机译:如今,人们在日常生活中忙于工作和其他事情,忽视了自己的健康。由于忙碌的生活和对健康的无知,生病的人数每天都在增加。此外,大多数人都患有心脏病之类的疾病。根据世界卫生组织(WHO)提供的数据,全球近31%的人口死于心脏病。因此,预测心脏病的发生与否成为医学领域的重要课题。然而,医疗部门或医院收到的数据非常庞大,有时难以分析。使用机器学习技术对数据进行预测和处理对于医务人员来说是非常有效的。因此,在这项研究中,我们讨论了心脏病及其危险因素,并解释了机器学习技术。利用这种机器学习技术,我们预测了心脏病,并对用于预测实验的机器学习算法进行了比较分析。这项研究的目的或目的完全与通过机器学习技术预测心脏病并对其进行分析有关。

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