Detection and diagnosis of chronic kidney disease using deep learning-based heterogeneous modified artificial neural network-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Detection and diagnosis of chronic kidney disease using deep learning-based heterogeneous modified artificial neural network

Published:2020-10 Issue: Volume:111 Page:17-26
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Ma Fuzhe,Sun Tao,Liu Lingyun,Jing Hongyu

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference25 articles.

1. Predictive analytics for chronic kidney disease using machine learning techniques;Charleonnan,2016

2. A predictive model for progression of chronic kidney disease to kidney failure;Tangri;JAMA,2011

3. Diagnosis of chronic kidney disease by using random forest;Subasi,2017

4. Detection of chronic kidney disease and selecting important predictive attributes;Salekin,2016

5. Cardiovascular mortality risk in chronic kidney disease: comparison of traditional and novel risk factors;Shlipak;JAMA,2005

Cited by 133 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. An Improved Adaptive Neuro-fuzzy Inference Framework for Lung Cancer Detection and Prediction on Internet of Medical Things Platform;International Journal of Computational Intelligence Systems;2024-09-02

2. An optimized fusion of deep learning models for kidney stone detection from CT images;Journal of King Saud University - Computer and Information Sciences;2024-09

3. A Biomedical Dataset Analysis on Predictive Modeling of Chronic Kidney Disease Using Machine Learning;Advances in Computational Intelligence and Robotics;2024-08-30

4. Blocking harmful images with a deep learning based next generation firewall;SIGMA J ENG NAT SCI;2024

5. Early detection of chronic kidney disease using eurygasters optimization algorithm with ensemble deep learning approach;Alexandria Engineering Journal;2024-08

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