Expert Systems with Applications: An International Journal
Computers in Biology and Medicine
Breast cancer diagnosis using least square support vector machine
Digital Signal Processing
A comparative study on thyroid disease diagnosis using neural networks
Expert Systems with Applications: An International Journal
A New Approach to Automated Epileptic Diagnosis Using EEG and Probabilistic Neural Network
ICTAI '08 Proceedings of the 2008 20th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
Computer-aided detection and diagnosis of breast cancer with mammography: recent advances
IEEE Transactions on Information Technology in Biomedicine
Automatic Detection of Arrhythmias Using Wavelets and Self-Organized Artificial Neural Networks
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural
Expert Systems with Applications: An International Journal
A GAs based approach for mining breast cancer pattern
Expert Systems with Applications: An International Journal
Intelligent hybrid modelling towards the prognosis of abdominal pain
International Journal of Hybrid Intelligent Systems - CIMA-08
Adaptive relevance matrices in learning vector quantization
Neural Computation
An Evolutionary Artificial Neural Network Approach for Breast Cancer Diagnosis
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
Artificial Intelligence Methods for Understanding Dynamic Computer Tomography Perfusion Maps
CISIS '10 Proceedings of the 2010 International Conference on Complex, Intelligent and Software Intensive Systems
A Novel Classification Method for Diagnosis of Diabetes Mellitus Using Artificial Neural Networks
DSDE '10 Proceedings of the 2010 International Conference on Data Storage and Data Engineering
An automatic diagnosis system based on thyroid gland: ADSTG
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Feature Selection for Medical Diagnosis Using Fuzzy Artmap Classification and Intersection Conflict
WAINA '10 Proceedings of the 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops
Fusion of fuzzy statistical distributions for classification of thyroid ultrasound patterns
Artificial Intelligence in Medicine
ECG beat classification using particle swarm optimization and radial basis function neural network
Expert Systems with Applications: An International Journal
Chest diseases diagnosis using artificial neural networks
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
AQTR '10 Proceedings of the 2010 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR) - Volume 02
An evolutionary artificial neural networks approach for breast cancer diagnosis
Artificial Intelligence in Medicine
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Automatic disease diagnosis systems have been used for many years. While these systems are constructed, the data used needs to be classified appropriately. For this purpose, a variety of methods have been proposed in the literature so far. As distinct from the ones in the literature, in this study, a general-purpose, fast and adaptive disease diagnosis system is developed. This newly proposed method is based on Learning Vector Quantization (LVQ) artificial neural networks which are powerful classification algorithms. In this study, the classification ability of LVQ networks is developed by embedding a reinforcement mechanism into the LVQ network in order to increase the success rate of the disease diagnosis method and reduce the decision time. The parameters of the reinforcement learning mechanism are updated in an adaptive way in the network. Thus, the loss of time due to incorrect selection of the parameters and decrement in the success rate are avoided. After the development process mentioned, the newly proposed classification technique is named ''Adaptive LVQ with Reinforcement Mechanism (ALVQ-RM)''. The method proposed handles data with missing values. To prove that this method did not offer a special solution for a particular disease, because of its adaptive structure, it is used both for diagnosis of breast cancer, and for diagnosis of thyroid disorders, and a correct diagnosis rate after replacing missing values using median method over 99.5% is acquired in average for both diseases. In addition, the success rate of determination of the parameters of the proposed ''LVQ with Reinforcement Mechanism (LVQ-RM)'' classifier, and how this determination affected the required number of iterations for acquiring that success rate are discussed with comparison to the other studies.