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Fuzzified Clustering and Point Set Continuous Approximation in Prognosticating Gastric Cancer Surgery

Authors:
Elisabeth Rakus-Andersson
Hang Zettervall

Keywords: c-means clustering; surgery degrees; clinical characteristic value; weights of importance; truncated π-functions.

Abstract:
We discuss two computational techniques in the current paper. In the first part, we aim at employing FCM (fuzzy c-means) clustering to compute membership degrees of two clusters providing decisions to perform surgery or not for a testing set of 25 gastric cancer patients. The second part handles mathematical modelling of a common function approximating the information obtained from the c-means procedure. After constructing the equation of the function, we can make the decision about the surgery in the form of the surgery degree for an arbitrary gastric cancer patient. A centre, dealing with mathematical techniques concerning surgery prognoses, can quickly decide about surgery for the patient who lives in a remote place. A transmission of information among the centre and some hospitals, interested in adopting the centre services, can facilitate surgery decision-making. This trial can be treated as a contribution in the telemedicine domain.

Pages: 158 to 163

Copyright: Copyright (c) IARIA, 2014

Publication date: March 23, 2014

Published in: conference

ISSN: 2308-4359

ISBN: 978-1-61208-327-8

Location: Barcelona, Spain

Dates: from March 23, 2014 to March 27, 2014