Original Contribution: Stacked generalization
Neural Networks
The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
A Mixture of Experts Network Structure for Breast Cancer Diagnosis
Journal of Medical Systems
Feature extraction from Doppler ultrasound signals for automated diagnostic systems
Computers in Biology and Medicine
Recurrent neural networks employing Lyapunov exponents for EEG signals classification
Expert Systems with Applications: An International Journal
A novel large-memory neural network as an aid in medical diagnosis applications
IEEE Transactions on Information Technology in Biomedicine
A combined neural network and decision trees model for prognosis of breast cancer relapse
Artificial Intelligence in Medicine
Model selection for a medical diagnostic decision support system: a breast cancer detection case
Artificial Intelligence in Medicine
Input feature selection for classification problems
IEEE Transactions on Neural Networks
Learning vector quantization for the probabilistic neural network
IEEE Transactions on Neural Networks
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
An expert system for detection of breast cancer based on association rules and neural network
Expert Systems with Applications: An International Journal
Combined neural networks for diagnosis of erythemato-squamous diseases
Expert Systems with Applications: An International Journal
Automated visual inspection expert system for multivariate statistical process control chart
Expert Systems with Applications: An International Journal
Combining recurrent neural networks with eigenvector methods for classification of ECG beats
Digital Signal Processing
New Artificial Metaplasticity MLP Results on Standard Data Base
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Breast Cancer Classification Applying Artificial Metaplasticity
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
Extended Gaussian kernel version of fuzzy c-means in the problem of data analyzing
Expert Systems with Applications: An International Journal
Detection of Resistivity for Antibiotics by Probabilistic Neural Networks
Journal of Medical Systems
Expert Systems with Applications: An International Journal
Diagnosis of breast cancer using hybrid magnetoacoustic method and artificial neural network
ACS'11 Proceedings of the 11th WSEAS international conference on Applied computer science
Neuro-fuzzy expert system for breast cancer diagnosis
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
Extended fuzzy c-means: an analyzing data clustering problems
Cluster Computing
| Hi-index | 12.06 |
This paper intends to an integrated view of implementing automated diagnostic systems for breast cancer detection. The major objective of the paper is to be a guide for the readers, who want to develop an automated decision support system for detection of breast cancer. Because of the importance of making the right decision, better classification procedures for breast cancer have been searched. The classification accuracies of different classifiers, namely multilayer perceptron neural network (MLPNN), combined neural network (CNN), probabilistic neural network (PNN), recurrent neural network (RNN) and support vector machine (SVM), which were trained on the attributes of each record in the Wisconsin breast cancer database, were compared. The purpose was to determine an optimum classification scheme with high diagnostic accuracy for this problem. This research demonstrated that the SVM achieved diagnostic accuracies which were higher than that of the other automated diagnostic systems.