Survival cluster analysis

@article{Chapfuwa2020SurvivalCA,
  title={Survival cluster analysis},
  author={Paidamoyo Chapfuwa and Chaojun Li and Nikhil Mehta and L. Carin and R. Henao},
  journal={Proceedings of the ACM Conference on Health, Inference, and Learning},
  year={2020}
}
  • Paidamoyo Chapfuwa, Chaojun Li, +2 authors R. Henao
  • Published 2020
  • Computer Science, Mathematics, Biology
  • Proceedings of the ACM Conference on Health, Inference, and Learning
  • Conventional survival analysis approaches estimate risk scores or individualized time-to-event distributions conditioned on covariates. In practice, there is often great population-level phenotypic heterogeneity, resulting from (unknown) subpopulations with diverse risk profiles or survival distributions. As a result, there is an unmet need in survival analysis for identifying subpopulations with distinct risk profiles, while jointly accounting for accurate individualized time-to-event… CONTINUE READING
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