An Application of Deep Belief Networks in Early Warning for Cerebrovascular Disease Risk
Author:
Affiliation:
1. Beijing Jiaotong University, China
2. China Unicom Research Institute, China
3. Rochester Institute of Technology, USA
Abstract
To reduce the incidence of cerebrovascular disease and mortality, identifying the risks of cerebrovascular disease in advance and taking certain preventive measures are significant. This article was aimed to investigate the risk factors of cerebrovascular disease (CVD) in the primary prevention, and to build an early warning model based on the existing technology. The authors use the information entropy algorithm of rough set theory to establish the index system suitable for early warning model. Then, using the limited Boltzmann machine and direction propagation algorithm, the depth trust network is established by building and stacking RBM, and the back propagation is used to fine-tune the parameters of the network at the top layer. Compared with the LM-BP early-warning model, the deep confidence network model is more effective than traditional artificial neural network, which can help to identify the risk of cerebrovascular disease in advance and promote the primary prevention.
Publisher
IGI Global
Subject
Strategy and Management,Computer Science Applications,Human-Computer Interaction
Reference22 articles.
1. The secondary prevention of small subcortical strokes (SPS3) Trial: Results of the blood pressure intervention.;O. R.Benavente;Lancet,2013
2. Artificial neural networks and robust Bayesian classifiers for risk stratification following uncomplicated myocardial infarction
3. Tratamiento hipolipemiante en la prevención secundaria de la enfermedad cerebrovascular isquémica
4. A Committee of Neural Networks for Traffic Sign Classification.;C.Dan;IJCNN,2011
5. A review of risk prediction models in cardiovascular disease: conventional approach vs. artificial intelligent approach
Cited by 8 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. A multi-modal integrated deep neural networks for the prediction of cardiovascular disease in type-2 diabetic males;Automatika;2023-10-02
2. A Two-Stage Emotion Generation Model Combining CGAN and pix2pix;Journal of Organizational and End User Computing;2023-09-21
3. Rehabilitation effect of intelligent rehabilitation training system on hemiplegic limb spasms after stroke;Open Life Sciences;2023-01-01
4. Safety Evaluation and Effect Deconstruction of Blood Lipid Test in the Diagnosis of Cardiovascular Disease Patients;BioMed Research International;2022-11-16
5. Deconstruction of Risk Prediction of Ischemic Cardiovascular and Cerebrovascular Diseases Based on Deep Learning;Contrast Media & Molecular Imaging;2022-09-30
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