• KARTHIKA K
• SOWMIYA P
• TAMILSELVAN SP
• Dr. SUDHA G

Breast cancer is one of the most highly invasive malignancies tumors that occurs in women and rarely in men . It is examined the worst cancer after lung cancer due to the higher death rate in women. Every year number of death is increasing extremely because of breast cancer. It is the most often type of all cancers and the major cause of death in women worldwide. Any development for prediction and diagnosis of cancer disease is most important for a healthy life. Accordingly, high accuracy in cancer prediction is important to update the treatment aspect and the survivability standard of patients. Breast mass classification systems are implemented using deep learning technologies such as a Convolutional Neural Network (CNN). CNN based systems have attained higher performance than the machine learning-based systems in the classification task of mammography images. The objective of this project is to collect and train the dataset, to predict the survival of patients with breast cancer. Based on the results, we can compare the performance of both ML and DL process (we implemented). To get the best model which is suitable for breast cancer detection.

CNN,Deep learning,Machine learning, Breast Cancer, Mammogram

"Automated Breast Mass Classification System Using Deep Learning and Ensemble learning in Digital Mammogram", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.e677-e688, September-2022, Available :http://www.jetir.org/papers/JETIR2209480.pdf

"Automated Breast Mass Classification System Using Deep Learning and Ensemble learning in Digital Mammogram", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppe677-e688, September-2022, Available at : http://www.jetir.org/papers/JETIR2209480.pdf