Heart Diseases Prediction using Deep Learning Neural Network Model

Author:

Abstract

Deep learning plays an important role in the field of medical science in solving health issues and diagnosing various diseases. So in this paper, we will discuss heart disease. We proposed a model for heart disease prediction. Heart Disease is on of key area where Deep Neural Network can be used so we can improve the overall quality of the classification of heart disease. The classification can be performed on the various ways like KNN, SVM, Naïve Bayes, Random Forest. Heart Disease UCI dataset will be used to demonstrate Talos Hyper-parameter optimization is more efficient than others.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Electrical and Electronic Engineering,Mechanics of Materials,Civil and Structural Engineering,General Computer Science

Cited by 58 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing Heart Disease Prediction using Advanced Feature Engineering and Ensemble Learning Techniques;International Journal of Advanced Research in Science, Communication and Technology;2024-02-06

2. Heart Disease Prediction and Prevention System;International Journal of Advanced Research in Science, Communication and Technology;2024-01-16

3. CNN-IKOA: convolutional neural network with improved Kepler optimization algorithm for image segmentation: experimental validation and numerical exploration;Journal of Big Data;2024-01-10

4. Enhancing Heart Disease Prediction Through a Heterogeneous Ensemble DL Models;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024

5. Classification models combined with Boruta feature selection for heart disease prediction;Informatics in Medicine Unlocked;2024

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3