Proceedings of the 16th Conference on Computer Science and Intelligence Systems

DOI: http://dx.doi.org/10.15439/2021F89

Citation: Proceedings of the 16th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 25, pages 301–311 (2021)

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Abstract. The log-rank test and Cox's proportional hazard model can be used to compare survival curves but are limited by strict statistical assumptions. In this study, we introduce a novel, assumption-free method based on a random forest algorithm able to compare two or more survival curves. A proportion of the random forest's trees with sufficient complexity is close to the test's p-value estimate. The pruning of trees in the model modifies trees' complexity and, thus, both the method's robustness and statistical power. The discussed results are confirmed using a simulation study, varying the survival curves and the tree pruning level.

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