Understanding Stroke in Dialysis and Chronic Kidney Disease

被引:9
|
作者
Rodrigues, Mariana [1 ]
Peixoto, Hugo [2 ]
Esteves, Marisa [2 ]
Machado, Jose [2 ]
Abelha [2 ]
机构
[1] Univ Minho, Campus Gualtar, P-4710 Braga, Portugal
[2] Univ Minho, Algoritmi Ctr, Campus Gualtar, P-4710 Braga, Portugal
来源
8TH INTERNATIONAL CONFERENCE ON EMERGING UBIQUITOUS SYSTEMS AND PERVASIVE NETWORKS (EUSPN 2017) / 7TH INTERNATIONAL CONFERENCE ON CURRENT AND FUTURE TRENDS OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN HEALTHCARE (ICTH-2017) / AFFILIATED WORKSHOPS | 2017年 / 113卷
关键词
Data Mining; Classification; Dialysis; Stroke Risk; Chronic Kidney Disease;
D O I
10.1016/j.procs.2017.08.296
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Patients with severe kidney failure need to be carefully monitored. One of the many treatments is called Continuous Ambulatory Peritoneal Dialysis (CAPD). This kind of treatment intends to maintain the blood tests as normal as possible. Data Mining and Machine Learning can take a simple and meaningless bloods test data set and build it into a Decision Support System. Through this article, Machine Learning algorithms will be explored with different Data Mining Models in order to extract knowledge and classify a patient with a stroke risk or not, according to their blood analysis. (c) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:591 / 596
页数:6
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