Prediction of Lung Diseases Using Deep Learning Models
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3191-6_37
Reference27 articles.
1. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/lung-cancer
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3. Rekha, H., Kumaravel, T., Natesan, P., Brinda, B.M., Sangeetha, S., Dharanesh, S.: Comparative study of deep learning techniques for automated classification of lung diseases. In: 2023 4th International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, pp. 1324–1328 (2023). https://doi.org/10.1109/ICOSEC58147.2023.10276053
4. Chen, H.-Y., Wang, H.-M., Lin, C.-H., Yang, R., Lee, C.-C.: Lung cancer prediction using electronic claims records: a transformer-based approach. IEEE J. Biomed. Health Inform. 27(12), 6062–6073 (2023). https://doi.org/10.1109/JBHI.2023.3324191
5. Jung, Y., Park, S., Sun, J.-M., Ahn, M.-J., Ahn, J.S., Lee, S.-H., Jung, H.A.: 1231PMachine learning prediction of the case-fatality of COVID-19 and risk factors for adverse outcomes in patients with non-small cell lung cancer. Ann. Oncol. 34(suppl. 2), S720 (2023). https://doi.org/10.1016/j.annonc.2023.09.2320. ISSN 0923-7534
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