[1] Giaquinto, AN., Sung, H., Newman, LA., Freedman, RA., Smith, RA., Star, J., et al. 2024. Breast cancer statistics. CA: a cancer journal for clinicians. 74(6):477-95.
[2] Mahmood, T., Li, J., Pei, Y., Akhtar, F., Imran, A., Rehman, KU.2020. A brief survey on breast cancer diagnostic with deep learning schemes using multi-image modalities. IEEe Access. 8:165779-809.
[3] Shahidi, F., Daud, SM., Abas, H., Ahmad, NA., Maarop, N. 2020. Breast cancer classification using deep learning approaches and histopathology image: A comparison study. Ieee Access. 8:187531-52.
[4] Balkenende, L., Teuwen, J., Mann, RM. 2022. editors. Application of deep learning in breast cancer imaging. Seminars in Nuclear Medicine; Elsevier.
[5] Li, X., Li, M., Yan, P., Li, G., Jiang, Y., Luo, H. et al. 2023. Deep learning attention mechanism in medical image analysis: Basics and beyonds. International Journal of Network Dynamics and Intelligence. 93- 116.
[6] Ding, R., Zhou, X., Tan, D., Su, Y., Jiang, C., Yu, G. et al. 2024. A deep multi-branch attention model for histopathological breast cancer image classification. Complex & Intelligent Systems. 10(3):4571-87.
[7] Souza, MD., Ananth Prabhu, G., Kumara, V. 2025. Advanced Breast Cancer Detection Using Spatial Attention and Neural Architecture Search (SANAS-Net). SN Computer Science. 6(1):1-12.
[8] Anari, S., Sadeghi, S., Sheikhi, G., Ranjbarzadeh, R., Bendechache, M. 2025. Explainable attention based breast tumor segmentation using a combination of UNet, ResNet, DenseNet, and EfficientNet models. Scientific Reports. 15(1):1027.
[9] Araújo, T., Aresta, G., Castro, E., Rouco, J., Aguiar, P., Eloy, C. et al. 2017. Classification of breast cancer histology images using convolutional neural networks. PloS one. 12(6):e0177544.
[10] Simonyan, EO., Badejo, JA., Weijin, JS. 2024. Histopathological breast cancer classification using CNN. Materials Today: Proceedings. 105:268-75.
[11] Wang, K., Liew, JH., Zou, Y., Zhou, D., Feng, J. 2019. editors. Panet: Few-shot image semantic segmentation with prototype alignment. proceedings of the IEEE/CVF international conference on computer vision.
[12] Fu, J., Liu, J., Tian, H., Li, Y., Bao, Y., Fang, Z. et al., 2019. editors. Dual attention network for scene segmentation. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.
[13] Toğaçar, M., Özkurt, KB., Ergen, B., Cömert, Z. 2020. BreastNet: A novel convolutional neural network model through histopathological images for the diagnosis of breast cancer. Physica A: Statistical Mechanics and its Applications. 545:123592.
[14] Zou, Y., Zhang, J., Huang, S., Liu, B. 2022. Breast cancer histopathological image classification using attention high‐order deep network. International Journal of Imaging Systems and Technology. 32(1):266-79.
[15] Toa, CK., Elsayed, M., Sim, KS. 2024. Deep residual learning with attention mechanism for breast cancer classification. Soft Computing. 28(15):9025-35.
[16] Li, X., Shen, X., Zhou, Y., Wang, X., Li, T-Q. 2020. Classification of breast cancer histopathological images using interleaved DenseNet with SENet (IDSNet). PloS one. 15(5):e0232127.
[17] Guo, C., Zhou, Q., Jiao, J., Li, Q., Zhu, L. 2024. A Modified MobileNetV3 Model Using an Attention Mechanism for Eight-Class Classification of Breast Cancer Pathological Images. Applied Sciences. 14(17):7564.
[18] Gautam, A., Singh, SK., editors. 2023. Analysis of Deep Learning Models to Detect Breast Cancer from Histopathology Images. TENCON 2023-2023 IEEE Region 10 Conference (TENCON); IEEE.
[19] Maleki, A., Raahemi, M., Nasiri, H. 2023. Breast cancer diagnosis from histopathology images using deep neural network and XGBoost. Biomedical Signal Processing and Control. 86:105152.
[20] Roy, S., Jain, PK., Tadepalli, K., Reddy, BP. 2024. Forward attention-based deep network for classification of breast histopathology image. Multimedia Tools and Applications. 1-30.
[21] Abdulaal, AH., Valizadeh, M., Albaker, BM., Yassin, RA., Amirani, MC., Shah, AS.2024. Enhancing Breast Cancer Classification using a Modified GoogLeNet Architecture with Attention Mechanism. Al-Iraqia Journal for Scientific Engineering Research. 3(1):47-63.
[22] Spanhol, FA., Oliveira, LS., Petitjean, C., Heutte, L., editors. 2016. Breast cancer histopathological image classification using convolutional neural networks. 2016 international joint conference on neural networks (IJCNN); IEEE.
[23] Wahab, N., Khan, A., Lee, YS. 2019. Transfer learning based deep CNN for segmentation and detection of mitoses in breast cancer histopathological images. Microscopy. 68(3):216-33.
[24] Davis, J., Goadrich, M., editors. 2006. The relationship between Precision-Recall and ROC curves. Proceedings of the 23rd international conference on Machine learning.
[25] Li, L., Jamieson, K., DeSalvo, G., Rostamizadeh, A., Talwalkar, A. 2018. Hyperband: A novel bandit-based approach to hyperparameter optimization. Journal of Machine Learning Research. 18(185):1-52.