Research on the Influencing factors of Heart Disease based on Binary Logistic Regression

Yuqi Guo
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Abstract

The main objective of this study was to analyze the multiple factors affecting heart disease using a binary logistic regression model. By examining the chart, this study draws many conclusions. Heart disease is at the forefront of mortality in China and even in the world. Thus, it is particularly important to explore its influencing factors. Through this study, chest pain type, resting electrocardiographic results, the slope of the peck exercise ST segment, and the maximum heart rate achieved were key factors affecting the occurrence of heart disease, and the prediction accuracy reached 86.05%, indicating that the conclusion is acceptable. The study provides more accurate strategies for the prediction of heart disease. This study fully explored the multiple influencing factors of heart disease; people should pay full attention to this indicator, maintain heart health, and be everyone’s responsibility. Protecting cardiovascular health is everyone’s responsibility. After all, health is the beginning of all work and good life.
基于二元逻辑回归的心脏病影响因素研究
本研究的主要目的是利用二元逻辑回归模型分析影响心脏病的多重因素。通过研究图表,本研究得出了许多结论。心脏病是中国乃至世界上死亡率最高的疾病。因此,探讨其影响因素尤为重要。通过本研究,胸痛类型、静息心电图结果、啄木鸟运动 ST 段斜率、达到的最大心率是影响心脏病发生的关键因素,预测准确率达到 86.05%,说明结论是可以接受的。该研究为心脏病的预测提供了更准确的策略。该研究充分挖掘了心脏病的多重影响因素,人们应充分重视这一指标,维护心脏健康,人人有责。保护心血管健康,人人有责。毕竟,健康是一切工作和美好生活的开始。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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