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Generating synthetic aging trajectories with a weighted network model using cross-sectional data
We develop a computational model of human aging that generates individual health trajectories with a set of observed health attributes. Our model consists of a network of interacting health attributes that stochastically damage with age to form health deficits, leading to eventual mortality. We trai...
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| Publicado no: | Sci Rep |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7670406/ https://ncbi.nlm.nih.gov/pubmed/33199733 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-76827-3 |
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