The DOI matches its Crossref record.
Survival ensembles
Abstract
We propose a unified and flexible framework for ensemble learning in the presence of censoring. For right-censored data, we introduce a random forest algorithm and a generic gradient boosting algorithm for the construction of prognostic and diagnostic models. The methodology is utilized for predicting the survival time of patients suffering from acute myeloid leukemia based on clinical and genetic covariates. Furthermore, we compare the diagnostic capabilities of the proposed censored data random forest and boosting methods, applied to the recurrence-free survival time of node-positive breast cancer patients, with previously published findings.
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Cited by
Ishwaran, H., Kogalur, U. B., Blackstone, E. H., & Lauer, M. S. (2008) · The Annals of Applied Statistics · doi:10.1214/08-aoas169 · Cited by 2,714
Post-fire vegetation and fuel development influences fire severity patterns in reburns
Coppoletta, M., Merriam, K. E., & Collins, B. M. (2016) · Ecological Applications · doi:10.1890/15-0225 · Cited by 295
Adams, S. E., Arnold, D., Murphy, B., Carroll, P., Green, A. K., Smith, A. M., Marsh, P. D., Chen, T., Marriott, R. E., & Brading, M. G. (2017) · Scientific Reports · doi:10.1038/srep43344 · Cited by 111
Estimating heterogeneous treatment effects with right-censored data via causal survival forests
Cui, Y., Kosorok, M. R., Sverdrup, E., Wager, S., & Zhu, R. (2023) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1093/jrsssb/qkac001 · Cited by 117
Lindberg, D. S., Prosperi, M., Bjarnadottir, R. I., Thomas, J., Crane, M., Chen, Z., Shear, K., Solberg, L. M., Snigurska, U. A., Wu, Y., et al. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104272 · Cited by 95
Metadata
- Authors
- Hothorn, T.
- Venue
- Biostatistics
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-12-20
- Volume
- 7
- Issue
- 3
- Pages
- 355-373
- ISSN
- 1465-4644 (ISSN-L)
- 1468-4357
- OpenAlex
- W4246259708
- Cited by
- 684
- References
- 0
- FWCI
- 4.99
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
