Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6204
Title: Adaptive Neuro-Fuzzy Inference Systems for Automatic Detection of Breast Cancer
Authors: Übeyli, Elif Derya
Keywords: Adaptive neuro-fuzzy inference system (ANFIS)
Fuzzy logic
Breast cancer
Issue Date: 2009
Publisher: Springer
Abstract: This paper intends to an integrated view of implementing adaptive neuro-fuzzy inference system (ANFIS) for breast cancer detection. The Wisconsin breast cancer database contained records of patients with known diagnosis. The ANFIS classifiers learned how to differentiate a new case in the domain by given a training set of such records. The ANFIS classifier was used to detect the breast cancer when nine features defining breast cancer indications were used as inputs. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the impacts of features on the detection of breast cancer were obtained through analysis of the ANFIS. The performance of the ANFIS model was evaluated in terms of training performances and classification accuracies and the results confirmed that the proposed ANFIS model has potential in detecting the breast cancer.
URI: https://doi.org/10.1007/s10916-008-9197-x
https://hdl.handle.net/20.500.11851/6204
ISSN: 0148-5598
1573-689X
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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