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Using Active Learning for Speeding up Calibration in Simulation Models
BACKGROUND: Most cancer simulation models include unobservable parameters that determine the disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality and their values are typically estimated via lengthy calibration proced...
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| Publicat a: | Med Decis Making |
|---|---|
| Autors principals: | , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2015
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4833719/ https://ncbi.nlm.nih.gov/pubmed/26471190 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/0272989X15611359 |
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