arXiv (All)
open access
Penalized Likelihood Optimization for Adaptive Neighborhood Clustering in Time-to-Event Data with Group-Level Heterogeneity
The identification of patient subgroups with comparable event-risk dynamics plays a key role in supporting informed decision-making in clinical research. In such settings, it is important to account for the inherent dependence that arises when individuals are nested within higher-level units, such a
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Instability in Patient Clustering: A Multiverse Analysis of Unsupervised Clustering in the CENTER-TBI cohort#985918
- Multidimensional spatiotemporal clustering -- An application to environmental sustainability scores in Europe#180518
- Multidimensional spatiotemporal clustering -- An application to environmental sustainability scores in Europe#179656
- Multidimensional spatiotemporal clustering -- An application to environmental sustainability scores in Europe#179261
- Multidimensional spatiotemporal clustering -- An application to environmental sustainability scores in Europe#179063
Record · ID 1156253
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive