Modeling the covariates effects on the hazard function by piecewise exponential artificial neural networks: an application to a controlled clinical trial on renal carcinoma

BACKGROUND: In exploring the time course of a disease to support or generate biological hypotheses, the shape of the hazard function provides relevant information. For long follow-ups the shape of hazard function may be complex, with the presence of multiple peaks. In this paper we present the use o...

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Detalles Bibliográficos
Autores principales: Fornili, Marco, Boracchi, Patrizia, Ambrogi, Federico, Biganzoli, Elia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069688/
https://www.ncbi.nlm.nih.gov/pubmed/30066658
http://dx.doi.org/10.1186/s12859-018-2179-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069688/
https://www.ncbi.nlm.nih.gov/pubmed/30066658
http://dx.doi.org/10.1186/s12859-018-2179-1

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