Review methods for breast cancer detection using artificial intelligence and deep learning methods
DOI:
https://doi.org/10.20535/SRIT.2308-8893.2021.1.08Keywords:
convolutional autoencoder, breast cancer detection, machine learning algorithms, convolutional neural networks, medical image classificationAbstract
Nowadays, there are many related works and methods that use Neural Networks to detect the breast cancer. However, usually they do not take into account the training time and the result of False Negative (FN) while training the model. The main idea of this paper is to compare already existing methods for detecting the breast cancer using Deep Learning Algorithms. Moreover, since the breast cancer is one of the most common lethal cancers and early detection helps prevent complications, we propose a new approach and the use of the convolutional autoencoder. This proposed model has shown high performance with sensitivity, precision, and accuracy of 93,50%, 91,60% and 93% respectively.
References
Breast Cancer Facts. Available: https://www.nationalbreastcancer.org/breast-cancer-facts
L. Shen et al., “Deep Learning to Improve Breast Cancer Detection on Screening Mammography”, Sci Rep, 9, 12495, 2019. Available: https://doi.org/10.1038/s41598-019-48995-4
S.A. Mohammed, S. Darrab, S.A. Noaman, and G. Saake, “Analysis of Breast Cancer Detection Using Different Machine Learning Techniques”, in Data Mining and Big Data. DMBD 2020. Communications in Computer and Information Science, vol. 1234, 2020. Springer, Singapore. Available: https://doi.org/ 10.1007/978-981-15-7205-0_10
Habib Dhahri, Eslam Al Maghayreh, Awais Mahmood, Wail Elkilani, and Mohammed Faisal Nagi, “Automated Breast Cancer Diagnosis Based on Machine Learning Algorithms”, Journal of Healthcare Engineering, vol. 2019, article ID 4253641, 11 pages, 2019. Available: https://doi.org/10.1155/2019/4253641.
Dalal Bardou, Kun Zhangi and Sayed Mohammad Ahmad, “Classification of Breast Cancer Based on Histology Images Using Convolutional Neural Networks”, 2018 IEEE, vol. 6, 2018.
Sandeep Chaurasia, Prasun Chakrabarti, and Neha Chourasia, “Prediction of Breast Cancer Biopsy Outcomes – An Approach using Machine Leaning Perspectives”, International Journal of Computer Applications, vol. 100, no.9, 2014.
Md. Milon Islam, Hasib Iqbal, Md. Rezwanul Haque, and Md. Kamrul Hasan, “Prediction of Breast Cancer Using Support Vector Machine and K-Nearest Neighbors”, 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 21–23 Dec 2017, Dhaka, Bangladesh.
Md. Kamrul Hasan and Tajwar Abrar Aleef, “Automatic Mass Detection in Breast Using Deep Convolutional Neural Network and SVM Classifier”, arXiv preprint arXiv:1907.04424v1 [cs.CV], 9 Jul 2019.
Yuriy P. Zaychenko, Kostiantyn A. Zdor, and Galib Hamidov, “Brain tumor diagnostics with application of hybrid fuzzy convolutional neural networks”, System Research and Information Technologies, no. 1, 2020. Available: https://doi.org/10. 20535/SRIT.2308-8893.2020.1.06.
