Improving the Accuracy of Predictive Models in Imbalanced Lung Cancer Data
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-7184-4_19
Reference15 articles.
1. Kumar, D., Gayap, H.T., Akhloufi, M.A.: Deep machine learning for medical diagnosis, application to lung cancer detection: a review. BioMedInformatics 4(1), 236–284 (2024)
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3. Bhuiyan, M.S., et al.: Advancements in early detection of lung cancer in public health: a comprehensive study utilizing machine learning algorithms and predictive models. J. Comput. Sci. Technol. Stud. 6(1), 113−121 (2024)
4. Shang, X., Zhang, C., Kong, R., Zhao, C., Wang, H.: Construction of a diagnostic model for small cell lung cancer combining metabolomics and integrated machine learning. Oncologist 29(3), e392–e401 (2024)
5. Linh, V.T., et al.: 3D plasmonic hexaplex paper sensor for label-free human saliva sensing and machine learning-assisted early-stage lung cancer screening. Biosen. Bioelectron. 244, 115779 (2024)
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