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Artificial bee colony (ABC) is one of the swarm intelligence optimization algorithms, inspired by foraging and dance behaviors of real honey bee colonies. This study is an instance of a hybrid algorithm using ABC together with k-nearest neighbor algorithm on diagnosis of coronary artery disease employing exercises stress test data. The study dataset is composed of 134 healthy and 346 unhealthy totally 480 patients. On the proposed algorithm two centroid vectors are obtained concerning one for healthy patients and the other for unhealthy patients utilizing ABC for the training part of the dataset. Then, the test part of the dataset is classified using k-nearest neighbor algorithm. The results obtained by the proposed technique show that this hybrid algorithm could be used as an alternative classifier on diagnosis of coronary artery disease employing exercise stress test data.