Application of Random Survival Forest in breast cancer survival analysis
DOI:
https://doi.org/10.59681/2175-4411.v15.iEspecial.2023.1113Keywords:
Breast Neoplasms, Machine Learning, Survival AnalysisAbstract
This paper aims to apply a supervised machine learning method to a clinical dataset from Zona da Mata Mineira, to evaluate the performance of survival prediction accuracy for breast cancer. The database utilized went through pre-processing providing the variables used in the Random Survival Forest. The results show satisfactor performance metrics for survival prediction methods. Concluding that, the machine learning methods are promising assisting and guiding clinical practice.
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Copyright (c) 2023 Daniela Schimitz de Carvalho, Thallys da Silva Nogueira, Priscila Vanessa Zabala Caprile Goliatt
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