Developing an Integrated Model Based on Regression Techniques in the Analysis of Individualized Predisposition to Cardiac Diseases

Anoushka Mongia
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Abstract

We have done a Logistic regression Model in this exploration paper using a heart dataset. In the first place, we used Linear regression. Be that as it may, it gave just a portion of the outcomes. So, we used Linear regression, which finally helped with anticipating whether or not a particular individual gets a respiratory problem. A respiratory failure, called myocardial enclosed putrefaction, happens when a piece of the heart muscle doesn't get adequate blood. The extra time slips by without treatment to restore the circulatory system, the more vital the damage to the heart muscle. Coronary vein ailment (computer-aided design) is the essential driver of cardiovascular failure. We endeavored to predict whether an individual gets respiratory disappointment by setting up a model with some heartrelated highlights.
基于回归技术的综合模型在个体化心脏病易感性分析中的应用
在这篇探索论文中,我们使用心脏数据集做了一个逻辑回归模型。首先,我们使用线性回归。尽管如此,它只给出了结果的一部分。所以,我们使用线性回归,这最终有助于预测一个特定的人是否有呼吸问题。当一块心肌得不到足够的血液时,就会发生呼吸衰竭,称为心肌封闭性腐烂。如果没有恢复循环系统的治疗,额外的时间就会流逝,对心肌的损害就越严重。冠状静脉疾病(计算机辅助设计)是心血管衰竭的主要驱动因素。我们试图通过建立一个带有一些心脏相关亮点的模型来预测个人是否会呼吸衰竭。
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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