Open Access
Issue |
ITM Web Conf.
Volume 44, 2022
International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
|
|
---|---|---|
Article Number | 03007 | |
Number of page(s) | 6 | |
Section | Computing | |
DOI | https://doi.org/10.1051/itmconf/20224403007 | |
Published online | 05 May 2022 |
- R. T. Sousa, O. Marques, F. A. A. Soares, I. I. Sene Jr, L. L. de Oliveira, and E. S. Spoto, “Comparative performance analysis of machine learning classifiers in detection of childhood pneumonia using chest radiographs, ” Procedia Computer Science, vol. 18, pp. 2579–2582 (2013). [CrossRef] [Google Scholar]
- W. H. Organization et al., “Standardization of interpretation of chest radiographs for the diagnosis of pneumonia in children, ” World Health Organization, Tech. Rep. (2001). [Google Scholar]
- J. De Fauw, J. R. Ledsam, B. Romera-Paredes, S. Nikolov, N. Tomasev, S. Blackwell, H. Askham, X. Glorot, B. O’Donoghue, D. Visentin et al., “Clinically applicable deep learning for diagnosis and referral in retinal disease, ” Nature medicine, vol. 24, no. 9, pp. 1342–1350, (2018). [CrossRef] [Google Scholar]
- R. E. Al Mamlook, S. Chen and H. F. Bzizi, “Investigation of the performance of Machine Learning Classifiers for Pneumonia Detection in Chest X-ray Images, ” 2020 IEEE International Conference on Electro Information Technology (EIT), pp. 098–104, doi: 10.1109/EIT48999.2020.9208232 (2022). [Google Scholar]
- Y. Dong, Y. Pan, J. Zhang and W. Xu, “Learning to Read Chest X-Ray Images from 16000+ Examples Using CNN, ” 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), 2017, pp. 51–57, doi: 10.1109/CHASE.2017.59. [CrossRef] [Google Scholar]
- M. S. Majdi, K. N. Salman, M. F. Morris, N. C. Merchant and J. J. Rodriguez, “Deep Learning Classification of Chest X-Ray Images, ” 2020 IEEE Southwest Symposium on Image Analysis and Interpretation (SsIAI), 2020, pp. 116–119, doi: 10.1109/SSIAI49293.2020.9094612. [CrossRef] [Google Scholar]
- Roshan Maur, “Imbalanced Tuberculosis and Pneumonia dataset, ” Kaggle.com, 2022. [Online]. Available: https://www.kaggle.com/roshanmaur/imbalanced-tuberculosis-and-pnuemo nia-dataset. [Accessed: 27-Feb-2022] [Google Scholar]
- Géron, A. Learning with Scikit-Learn, Keras & TensorFlow. 2nd ed. O'Reilly Media, Inc., p. 422. (2019) [Google Scholar]
- Wikipedia Contributors, “List of hospitals in India,” Wikipedia, 17-Feb-2022. [Online]. Available: https://en.wikipedia.org/wiki/List_of_hospitals_in_India. [Accessed: 27-Feb-2022] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.