Learning fuzzy grey cognitive maps using nonlinear hebbian-based approach

 
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2012 (EN)
Learning fuzzy grey cognitive maps using nonlinear hebbian-based approach (EN)

Παπαγεωργίου, Ελπινίκη Ι. (EL)
Salmeron, Jose L. (EN)

Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε. (EL)

Recently, Fuzzy Grey Cognitive Maps (FGCM) has been proposed as a FCM extension. It is based on Grey System Theory, that it has become a very effective theory for solving problems within environments with high uncertainty, under discrete small and incomplete data sets. The proposed approach of learning FGCMs applies the Nonlinear Hebbian based algorithm determine the success of radiation therapy process estimating the final dose delivered to the target volume. The scope of this research is to explore an alternative decision support method using the main aspects of fuzzy logic and grey systems to cope with the uncertainty inherent in medical domain and physicians uncertainty to describe numerically the influences among concepts in medical domain. The Supervisor-FGCM, trained by NHL algorithm adapted in FGCMs, determines the treatment variables of cancer therapy and the acceptance level of final radiation dose to the target volume. Three clinical case studies were used to test the proposed methodology with meaningful and promising results and prove the efficiency of the NHL algorithm for FGCM approach. (EN)

journalArticle

Βιοϊατρική μηχανική (EN)
Fuzzy cognitive maps (EN)
Biomedical engineering (EN)
Ασαφή γνωστικά (EN)

ΤΕΙ Αθήνας (EL)
Technological Educational Institute of Athens (EN)

International Journal of Approximate Reasoning (EN)

English

2012

doi:10.1016/j.ijar.2011.09.006

Elsevier Inc (EN)



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