Tan, F.; Zhou, Y.; Li, S.; Jiang, C.; Zhou, J.-G.; Bellur, S.
An RMST-Integrated Machine Learning Framework for Interpretable Survival Analysis Under Non-Proportional Hazards: Application to the METABRIC Cohort. Algorithms 2026, 19, 329.
https://doi.org/10.3390/a19050329
AMA Style
Tan F, Zhou Y, Li S, Jiang C, Zhou J-G, Bellur S.
An RMST-Integrated Machine Learning Framework for Interpretable Survival Analysis Under Non-Proportional Hazards: Application to the METABRIC Cohort. Algorithms. 2026; 19(5):329.
https://doi.org/10.3390/a19050329
Chicago/Turabian Style
Tan, Fangya, Yang Zhou, Shuqiao Li, Chun Jiang, Jian-Guo Zhou, and Srikar Bellur.
2026. "An RMST-Integrated Machine Learning Framework for Interpretable Survival Analysis Under Non-Proportional Hazards: Application to the METABRIC Cohort" Algorithms 19, no. 5: 329.
https://doi.org/10.3390/a19050329
APA Style
Tan, F., Zhou, Y., Li, S., Jiang, C., Zhou, J.-G., & Bellur, S.
(2026). An RMST-Integrated Machine Learning Framework for Interpretable Survival Analysis Under Non-Proportional Hazards: Application to the METABRIC Cohort. Algorithms, 19(5), 329.
https://doi.org/10.3390/a19050329