A Hierarchical Bayesian Model for the Identification of PET Markers Associated to the Prediction of Surgical Outcome after Anterior Temporal Lobe Resection

We develop an integrative Bayesian predictive modeling framework that identifies individual pathological brain states based on the selection of fluoro-deoxyglucose positron emission tomography (PET) imaging biomarkers and evaluates the association of those states with a clinical outcome. We consider...

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Detalhes bibliográficos
Publicado no:Front Neurosci
Main Authors: Chiang, Sharon, Guindani, Michele, Yeh, Hsiang J., Dewar, Sandra, Haneef, Zulfi, Stern, John M., Vannucci, Marina
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2017
Assuntos:
Neuroscience
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5723403/
https://ncbi.nlm.nih.gov/pubmed/29259537
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2017.00669
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