Al-Sammarraie, Luay Hani AbbasIbrahim, Abdullahi Abdu2021-05-152021-05-1520209781728190907https://doi.org/10.1109/ISMSIT50672.2020.9254891https://hdl.handle.net/20.500.12939/10554th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 -- 22 October 2020 through 24 October 2020 -- -- 165025Breast cancer is the second leading cause of cancer death in women in the world. Statistics show that 1, 152, 161 new cases of breast cancer are found worldwide; and with 411, 093 deaths It has been shown that early diagnosis of breast cancer increases the probability of a complete recovery and reduces the mortality of patients suffering from this cancer [1] Cancer is the mutation of genes responsible for cell replication and the regulation of cell growth. These genes are found in the nucleus of cells and act as a control to turn different cells on or off so that old cells die while new ones take over. When a mutation occurs, these cells do not die and begin to divide uncontrollably, creating tumors in this work we have designed and implemented a system whose main purpose is to detect the existence of breast cancer lumps in fine needle aspiration images. We use a clustering and a feature extraction method such as CNN and then we use a classification method to detect the cancer. Early detection of breast cancer is essential to increase patient survival © 2020 IEEE.eninfo:eu-repo/semantics/closedAccessBreast CancerCNNFine Needle AspirationMachine LearningConference Object10.1109/ISMSIT50672.2020.92548912-s2.0-85097662949N/A