A proposed heart disease diagnosis based on Deep learning.

M. ELBouridy, A. EL-Batouty, Marwa E Samara, Wael Abouelwafa Ahmed, Mohamed Massoud
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Abstract

: One of the most influential factors in preserving a person's life is the late detection of heart disease, as cardiovascular disease is considered one of the biggest risks that lead to death. Cholesterol level, age, gender, as well as blood sugar level and heart rate are considered among the most influential factors in heart disease. The accurate diagnosis of all these diseases depends on the experience and skill of the treating physician. Many researchers have intended to use automated methods to diagnose diseases without relying on the expertise of doctors. In this research, the researchers present a proposal based on deep learning (DL) using the distinctive features of some factors affecting heart disease. Therefore, magnification techniques were used to diagnose whether the patient is at risk for cardiovascular disease. Bloody or not. The research resulted in progress, as accuracy in diagnosis reached 90.088%.
基于深度学习的心脏病诊断建议。
:心血管疾病被认为是导致死亡的最大风险之一,而心脏病的晚期发现是保护人的生命的最有影响力的因素之一。胆固醇水平、年龄、性别、血糖水平和心率被认为是心脏病的最大影响因素。所有这些疾病的准确诊断都取决于主治医生的经验和技术。许多研究人员打算使用自动方法来诊断疾病,而不依赖医生的专业知识。在这项研究中,研究人员提出了一项基于深度学习(DL)的建议,利用影响心脏病的一些因素的显著特征。因此,放大技术被用来诊断病人是否有患心血管疾病的风险。血腥与否。研究取得了进展,诊断准确率达到 90.088%。
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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