DocumentCode
3537982
Title
A data mining approach to fistula surgery failure analysis in hemodialysis patients
Author
Sepehri, Mohammad Mehdi ; Khavaninzadeh, Morteza ; Rezapour, Mohammad ; Teimourpour, Babak
Author_Institution
Sch. of Eng., Tarbiat Modares Univ., Tehran, Iran
fYear
2011
fDate
14-16 Dec. 2011
Firstpage
15
Lastpage
20
Abstract
Patients with End-stage renal disease (ESRD) require hemodialysis (HD). An important aspect of HD treatment is vascular access, which that arterio-venous fistula (AVF) is the most desirable form of it. In this study we analyze the attributes of early Failure AVFs. The main idea is using descriptive techniques of data mining -such as Clustering- to discover important factors of them.
Keywords
data mining; diseases; failure analysis; surgery; HD treatment; arteriovenous fistula; clustering; data mining; end stage renal disease; fistula surgery failure analysis; hemodialysis patients; vascular access; Biomedical engineering; Clustering algorithms; Data mining; Data models; Educational institutions; High definition video; Surgery; Clustering; Data Mining; Early failure; Fistula; Hemodialysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering (ICBME), 2011 18th Iranian Conference of
Conference_Location
Tehran
Print_ISBN
978-1-4673-1004-8
Type
conf
DOI
10.1109/ICBME.2011.6168546
Filename
6168546
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