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Showing 1 to 4 of 4 for “"random survival forests"”.
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Random survival forests: quantifying uncertainties and other extensions
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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Survival analysis for lung cancer patients
… usually has a poor prognosis, with a five years survival rate of only 21% according to the SEER Cancer Statistics Review, 1975-2017. With such a deadly disease, it is crucial to predict the survival likelihood of cancer patients. However, this is not an easy task due to the many factors affecting …
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Comparative Analysis of Discrimination and Calibration Accuracy of Discrete Survival, Random Forests, and Neural Networks in Health-Related Survival Prediction Models
Prediction models for survival analysis are commonly used in biomedical sciences to understand the onset of certain diseases. Traditional statistical models have been employed for the previous years, however, their limitations and inability to handle big data sets has made a way for the …
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Three Essays on Machine Learning in Empirical Finance
… fit on managerial tenure is causal using random survival forests. Firms that hire culturally disruptive managers have lower future market values and performance. The stock market reacts positively to signals that indicate low cultural dispersion within the firm. In the second paper, we …