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Dynamic Prediction in Clinical Survival Analysis
Abstract
There is a huge amount of literature on statistical models for the prediction of survival after diagnosis of a wide range of diseases like cancer, cardiovascular disease, and chronic kidney disease. Current practice is to use prediction models based on the Cox proportional hazards model and to present those as static models for remaining lifetime a
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Metadata
- Authors
- van Houwelingen, H., & Putter, H.
- Venue
- CRC Press eBooks
- Publisher
- CRC Press
- Published
- 2011-11-09
- OpenAlex
- W628731042
- Cited by
- 344
- References
- 0
- FWCI
- 3.47
- Type
- book
- Language
- en
- Open access
- closed
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- van Houwelingen, H., & Putter, H. (2011). Dynamic Prediction in Clinical Survival Analysis. CRC Press eBooks. https://doi.org/10.1201/b11311
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
