Bayesian probit regression model for the diagnosis of pulmonary fibrosis: proof-of-principle

BACKGROUND: The accurate diagnosis of idiopathic pulmonary fibrosis (IPF) is a major clinical challenge. We developed a model to diagnose IPF by applying Bayesian probit regression (BPR) modelling to gene expression profiles of whole lung tissue. METHODS: Whole lung tissue was obtained from patients...

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Detalles Bibliográficos
Autores principales: Meltzer, Eric B, Barry, William T, D'Amico, Thomas A, Davis, Robert D, Lin, Shu S, Onaitis, Mark W, Morrison, Lake D, Sporn, Thomas A, Steele, Mark P, Noble, Paul W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3199230/
https://www.ncbi.nlm.nih.gov/pubmed/21974901
http://dx.doi.org/10.1186/1755-8794-4-70

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3199230/
https://www.ncbi.nlm.nih.gov/pubmed/21974901
http://dx.doi.org/10.1186/1755-8794-4-70

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