Publisher
Springer Nature Switzerland
Reference43 articles.
1. Agchung: Covid-19 chest x-ray dataset initiative, visited on march-01st-2022 (2022). https://github.com/agchung/Figure1-COVID-chestxray-dataset
2. Ahmad, F., Ghani Khan, M.U., Javed, K.: Deep learning model for distinguishing novel coronavirus from other chest related infections in x-ray images. Comput. Biol. Med. 134, 104401 (2021). https://doi.org/10.1016/j.compbiomed.2021.104401, https://www.sciencedirect.com/science/article/pii/S0010482521001955
3. Arora, R., et al.: AI-based diagnosis of COVID-19 patients using x-ray scans with stochastic ensemble of CNNs. Phys. Eng. Sci. Med. 44, 1257–1271 (2021). https://doi.org/10.1007/s13246-021-01060-9, https://link.springer.com/article/10.1007/s13246-021-01060-9
4. Asraf, A.: Covid19 with pneumonia and normal chest xray(pa) dataset, visited on may-6th-2022 (2022). https://www.kaggle.com/amanullahasraf/covid19-pneumonia-normal-chest-xraypa-dataset
5. Avetisian, M., et al.: CORSAI: a system for robust interpretation of CT scans of COVID-19 patients using deep learning. ACM Trans. Manage. Inf. Syst. 12(4) (2021). https://doi.org/10.1145/3467471
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献