Optimized Prognostic Models for Oral Cancer Survival using Feature Selection Methods
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Publisher
Elsevier BV
Reference14 articles.
1. Zhang, S. Z., Xie, L., & Shang, Z. J. (2022) “Burden of Oral Cancer on the 10 Most Populous Countries from 1990 to 2019: Estimates from the Global Burden of Disease Study 2019.” International journal of environmental research and public health 19(2): 875-888.
2. Ribeiro, I. P., Barroso, L., Marques, F., Melo, J. B., & Carreira, I. M. (2016) “Early detection and personalized treatment in oral cancer: the impact of omics approaches.” Molecular cytogenetics 9: 85-92.
3. Zanella, L., Facco, P., Bezzo, F., & Cimetta, E. (2022) “Feature Selection and Molecular Classification of Cancer Phenotypes: A Comparative Study.” International journal of molecular sciences 23(16): 9087-9108.
4. Muthukrishnan, R., & Rohini, R. (2016) “LASSO: A feature selection technique in predictive modeling for machine learning” International conference on advances in computer applications (ICACA) IEEE 18-20.
5. Liu, J., Liang, G., Siegmund, K. D., & Lewinger, J. P. (2018) “Data integration by multi-tuning parameter elastic net regression.” BMC Bioinformatics 19(1): 1-9.
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