Abed moharamy - Department of Computer Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran
Mehdi Sadeghzadeh - Department of Computer Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran

Nowadays, there can hardly be found any person how is not aware of irreversible percautions of false or late diagnosis in medical sciences. Such a matter can lead to inrecaverable situations or maybe patient death. Because of the mentioned sensitivity in this area, many researchers has been focused to develop other intelligent techniques to be employed in medical diagnosis. Data mining is one of them. In this regard, the current research aimed at developing a new combined technique based on fuzzy C-means clustering and Ant Colony optimization to improve the accuracy of heart disease prediction. The main concentration of this thesis is limited to Arhythmia; however the proposed schme can be employed in other disciplines. According to the numerical results, the novel technique achived acceptable measures in terms of the accuracy; where, 81.82% of accuracy is obtained.

Arhythmia; Classification; Supervised Learning; C-means; Ant Colony