A decision support tool for the diagnosis of breast cancer based upon Fuzzy ARTMAP |
| |
Authors: | J. Downs R. F. Harrison S. S. Cross |
| |
Affiliation: | (1) Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, S1 3JD Sheffield, UK;(2) Department of Pathology, University of Sheffield Medical School, Sheffield, UK |
| |
Abstract: | This paper presents research into the application of the fuzzy ARTMAP neural network model to the diagnosis of cancer from fine-needle aspirates of the breast. Trained fuzzy ARTMAP networks are differently pruned so as to maximise accuracy, sensitivity and specificity. The differently pruned networks are then employed in a cascade of networks intended to separate cases into certain and suspicious classes. This mimics the predictive behaviour of a human pathologist. The fuzzy ARTMAP model also provides symbolic rule extraction facilities and the validity of the derived rules for this domain is discussed. Additionally, results are provided showing the effects upon network performance of different input features and different observers. The implications of the findings are discussed. |
| |
Keywords: | Artificial neural networks Breast cancer Fuzzy ARTMAP Symbolic rule extraction |
本文献已被 SpringerLink 等数据库收录! |