en Supportive and Palliative Care Original/Research Article <div style="text-align: justify;"><span style="font-size:14px;"><span style="font-family:Times New Roman;"><strong>Introduction: </strong>The early diagnosis of breast cancer as prevalent cancer among women, is a necessity in the research on cancers since it could simplify the clinical management of other patients. The importance of the classification of breast cancer patients into high- or low-risk groups has led research groups in the biomedical and informatics departments to evaluate and use computer techniques such as data mining. To date, various methods have been used for breast cancer diagnosis which has shown unfavorable accuracy due to issues such as computational complexities and prolonged implementation.<br> <strong>Methods: </strong>The present study aimed to apply the feature selection method based on the binary bat algorithm (BBA) to increase the accuracy of the breast cancer diagnosis. Feature selection is carried out to select the most important features from a dataset. We applied the na&iuml;ve bayes (NB), support vector machine (SVM), and J48 algorithms in MATLAB software; based on the dataset obtained from Wisconsin to evaluate the accuracy, sensitivity, and diagnostic criteria of the proposed model.<br> <strong>Results: </strong>The BBA had 99.28%, 96.43%, and 92.86% accuracy in SVM, NB and J48 algorithms, respectively.<br> <strong>Conclusions: </strong>According to the results, the feature selection technique, along with the BBA and SVM, yielded the most accurate results regarding breast cancer detection.</span></span></div> Data Mining, Breast Neoplasms, Support Vector Machine, Binary Bat, Algorithms 1 7 http://mcijournal.com/browse.php?a_code=A-10-372-2&slc_lang=en&sid=1 Reyhaneh Yaghoubzadeh yaghobzdehr@gmail.com 10031947532846002821 10031947532846002821 Yes Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran Seyed Reza Kamel rezakamel@computer.org 10031947532846002822 10031947532846002822 No Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran Hossain Barzgar hossain.bar68@gmail.com 10031947532846002823 10031947532846002823 No Department of Computer Sciences, Islamic Azad University, Neyshabur Branch, Neyshabur, Iran Bahare Moshajeri San’ati baharsnt@yahoo.com 10031947532846002824 10031947532846002824 No Department of Computer Sciences, Islamic Azad University, Neyshabur Branch, Neyshabur, Iran