Title :
Adaptive neuro-fuzzy inference system (ANFIS) in modelling breast cancer survival
Author :
Hamdan, Hazlina ; Garibaldi, Jonathan M.
Author_Institution :
Intell. Modelling & Anal. (IMA) Res. Group, Univ. of Nottingham, Nottingham, UK
Abstract :
Medical prognosis is the prediction of the future course and outcome of a disease and an indication of the likelihood of recovery from that disease. Soft-computing approaches including artificial neural networks and fuzzy inference have been used widely to model expert behaviour. In this paper, we propose the use of an adaptive fuzzy inference system (ANFIS) technique in the estimation of survival prediction. This paper describes the methodology by which ANFIS was used to model survival and presents a comparison of this new method with existing methods in the capability to predict the survival rate in a given medical data set concerning survival of patients following operative surgery for breast cancer.
Keywords :
cancer; fuzzy reasoning; medical computing; neural nets; surgery; ANFIS; adaptive neuro fuzzy inference system; artificial neural networks; breast cancer survival modeling; fuzzy inference; medical prognosis; operative surgery; soft computing approaches; Adaptation model; Artificial neural networks; Breast cancer; Data models; Diseases; Hazards; Training;
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6919-2
DOI :
10.1109/FUZZY.2010.5583997