Author:
Balaji A.,Rajakumari S. Brintha
Publisher
Springer Nature Switzerland
Reference26 articles.
1. Kido, S., Hirano, Y., Hashimoto, N.: Detection and classification of lung abnormalities by use of convolutional neural network (CNN) and regions with CNN features (R-CNN). In: International Workshop on Advanced İmage Technology (IWAIT), Chiang Mai, Thailand, pp. 1–42018. IEEE (2018)
2. Mondal, M.R.H., Bharati, S., Podder, P., Podder, P.: Data analytics for novel coronavirus disease. İnform. Med. Unlocked 20, 1–13 (2020)
3. Kuan, K., et al.: Deep learning for lung cancer detection: tackling the kaggle data science bowl 2017 challenge, pp. 1–9. arXiv preprint arXiv:1705.09435 (2017)
4. Sun, W., Zheng, B., Qian, W.: Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis. Comput. Biol. Med. 89, 530–539 (2017)
5. Sun, W., Zheng, B., Qian, W.: Computer aided lung cancer diagnosis with deep learning algorithms. In: Medical İmaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, vol. 9785, pp. 241–248 (2016)