Smart Doctor: Performance of Supervised ART-I Artificial Neural Network for Breast Cancer Diagnoses
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Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.
2009 ◽
Vol 116
(4)
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pp. 690-692
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2015 ◽
Vol 5
(1)
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pp. 26-32
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2016 ◽
Vol 4
(11)
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pp. 598-610
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