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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...
Αποθηκεύτηκε σε:
| Τόπος έκδοσης: | Front Neurosci |
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| Κύριοι συγγραφείς: | , , , , , , |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
Frontiers Media S.A.
2017
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| Θέματα: | |
| Διαθέσιμο Online: | 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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