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Thyroid Disease Diagnosis using Genetic Algorithm and Neural Network | ||
| Journal of Al-Qadisiyah for Computer Science and Mathematics | ||
| Article 1, Volume 3, Issue 2, 2011, Pages 1-13 PDF (0 K) | ||
| Author | ||
| Sarah Behnam Aziz | ||
| Abstract | ||
| Abstract: Nowadays, with advancement of technology and science and expansion of computer usage in high-tech calculations, especially in the field of medicine, intelligence systems and in particular Neural Networks are becoming of significant importance in automatic diagnosis and prognoses of different diseases. This paper presents the diagnosis of thyroid diseases using Neural Networks. The genetic algorithm was used to find the optimum network structure with high classification accuracy. The experimental results presented for different proportions of training/testing groups show a high classification accuracy and convergence in rates. The overall accuracy is 100% for training and in range between 96% and 98% for testing. The neural networks are simulated using MATLAB. While thyroid disease datasets are taken from UCI machine learning dataset. | ||
| Keywords | ||
| thyroid diseases; neural networks; Fast Learning Algorithms; genetic algorithm | ||
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