Publication: Comparison of neuro-fuzzy based techniques in nasopharyngeal carcinoma recurrence prediction
Issued Date
2009-12-10
Resource Type
ISSN
10987584
Other identifier(s)
2-s2.0-71249111926
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
IEEE International Conference on Fuzzy Systems. (2009), 1199-1203
Suggested Citation
Orrawan Kumdee, Hirosato Seki, Hiroaki Ishii, Thongchai Bhongmakapat, Panrasee Ritthipravat Comparison of neuro-fuzzy based techniques in nasopharyngeal carcinoma recurrence prediction. IEEE International Conference on Fuzzy Systems. (2009), 1199-1203. doi:10.1109/FUZZY.2009.5277085 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/27450
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Comparison of neuro-fuzzy based techniques in nasopharyngeal carcinoma recurrence prediction
Other Contributor(s)
Abstract
This paper aims to compare neuro-fuzzy based techniques for effective prediction of nasopharyngeal carcinoma (NPC) recurrence. The techniques include an artificial neural network (ANN), adaptive neuro-fuzzy inference systems (ANFIS), the functional-type single input rule modules connected fuzzy inference method (F-SIRMs method) and the functional and neural network type SIRMs method (F-NN-SIRMs method). All models are produced to predict the presence or absence and timing of the NPC recurrence. Five years predictions are carried out. Validity of each predictive model is assured by 10-fold cross validation. The results show that the F-NN-SIRMs method is superior to the other techniques in a sense that it provides the higher prediction performance. ©2009 IEEE.