<![CDATA[Abstract Breast cancer threatens the female population worldwide. Prevention with early detection of this disease is essential in reducing mortality. The primary purpose of this study is to analyze the classification of breast cancer and determine the categories of normal and malignant cancers with computer-assisted detection and diagnosis (CAD) to detect the disease immediately. In this study, we offer a prototype of a breast cancer classification system using a digital mammogram method based on comparing the collaboration features of the Histogram and Gray Level Co-occurrence Matrix (GLCM). The results of this study indicate that the level of accuracy reached the value of 97.67%, sensitivity 98.40%, specificity 97.63%, and ROC 97.70%. This study serves to assist radiologists as a consideration in making decisions.]]>
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