Predicting technique survival in peritoneal dialysis patients: comparing artificial neural networks and logistic regression
Author:
Publisher
Oxford University Press (OUP)
Subject
Transplantation,Nephrology
Link
http://academic.oup.com/ndt/article-pdf/23/9/2972/7632254/gfn187.pdf
Reference37 articles.
1. ESRD patients in 2004: global overview of patient numbers, treatment modalities and associated trends
2. Comparison of Hemodialysis and Peritoneal Dialysis — a Cost–Utility Analysis
3. Comparison of hemodialysis and peritoneal dialysis survival in The Netherlands
4. Patient Ratings of Dialysis Care With Peritoneal Dialysis vs Hemodialysis
5. Predicting a patient's choice of dialysis modality:Experience in a United Kingdom renal department
Cited by 38 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. CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation Using Graph Neural Networks;Journal of Healthcare Informatics Research;2024-08-01
2. Artificial intelligence and machine learning in peritoneal dialysis: a systematic review of clinical outcomes and predictive modeling;International Urology and Nephrology;2024-07-06
3. Human face identification after plastic surgery using SURF, Multi-KNN and BPNN techniques;Complex & Intelligent Systems;2024-03-13
4. The Peritoneal Dialysis Surprise Question and Technique Survival: Are you surprised?;Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis;2024-01
5. Predicting transfer to haemodialysis using the peritoneal dialysis surprise question;Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis;2023-11-28
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