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Applied Fuzzy C-means Clustering to Operation Evaluation for Gastric Cancer Patients
Blekinge Institute of Technology, School of Engineering, Department of Mathematics and Natural Sciences.
Blekinge Institute of Technology, School of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-9920-7946
2013 (English)Conference paper (Refereed) Published
Abstract [en]

Like data analysis, pattern recognition and data mining, fuzzy clustering also has been applied widely, and successful applications have been reported. In this paper we aim to employ the technique of fuzzy c-means (FCM) cluster to prognosticate the operation possibility on gastric cancer patients. Our purpose is to partition some clinical data in two fuzzy clusters. One of them considers patients who have a chance for successful surgery whereas the other cluster contains the patients without a view for surgery. Each patient is given by characteristic biological markers. The initial values of membership degrees taking place in the partition matrix are usually determined randomly. In this work we will use particularly designed membership functions to calculate the degrees of membership.

Place, publisher, year, edition, pages
Nice, France: IARIA , 2013.
Keyword [en]
Fuzzy C-means clustering analysis, Fuzzy partition, Operation decision
National Category
Mathematics Medical and Health Sciences
Identifiers
URN: urn:nbn:se:bth-7007Local ID: oai:bth.se:forskinfo71884F5A9AEDD407C1257B2B00614E0AISBN: 978-1-61208-252-3OAI: oai:DiVA.org:bth-7007DiVA: diva2:834578
Conference
The Fifth International Conference on eHealth, Telemedicine, and Social Medicine - eTELEMED 2013
Available from: 2013-03-12 Created: 2013-03-11 Last updated: 2016-09-20Bibliographically approved

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Zettervall, HangRakus-Andersson, Elisabeth
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