Random survival forests for the analysis of recurrent events for right-censored data, with or without a terminal event
- DOI
- 10.1186/s12874-025-02678-z
- Published
- 2025-11-20
- Container
- BMC Medical Research Methodology
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s12874-025-02678-z,
title = {Random survival forests for the analysis of recurrent events for right-censored data, with or without a terminal event},
author = {Juliette Murris and Olivier Bouaziz and Michal Jakubczak and Sandrine Katsahian and Audrey Lavenu},
year = {2025},
journal = {BMC Medical Research Methodology},
doi = {10.1186/s12874-025-02678-z},
url = {https://doi.org/10.1186/s12874-025-02678-z}
}RIS
TY - JOUR TI - Random survival forests for the analysis of recurrent events for right-censored data, with or without a terminal event AU - Juliette Murris AU - Olivier Bouaziz AU - Michal Jakubczak AU - Sandrine Katsahian AU - Audrey Lavenu PY - 2025 JO - BMC Medical Research Methodology DO - 10.1186/s12874-025-02678-z UR - https://doi.org/10.1186/s12874-025-02678-z ER -
APA
Murris, J., Bouaziz, O., Jakubczak, M., Katsahian, S., & Lavenu, A. (2025). Random survival forests for the analysis of recurrent events for right-censored data, with or without a terminal event. BMC Medical Research Methodology. https://doi.org/10.1186/s12874-025-02678-z
Source records
- crossref · retrieved 2026-09-26T08:24:44.470Z