Robust automated computational approach for classifying frontotemporal neurodegeneration: Multimodal/multicenter neuroimaging

INTRODUCTION: Timely diagnosis of behavioral variant frontotemporal dementia (bvFTD) remains challenging because it depends on clinical expertise and potentially ambiguous diagnostic guidelines. Recent recommendations highlight the role of multimodal neuroimaging and machine learning methods as comp...

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Detalles Bibliográficos
Autores principales: Donnelly-Kehoe, Patricio Andres, Pascariello, Guido Orlando, García, Adolfo M., Hodges, John R., Miller, Bruce, Rosen, Howie, Manes, Facundo, Landin-Romero, Ramon, Matallana, Diana, Serrano, Cecilia, Herrera, Eduar, Reyes, Pablo, Santamaria-Garcia, Hernando, Kumfor, Fiona, Piguet, Olivier, Ibanez, Agustin, Sedeño, Lucas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Diagnostic Assessment & Prognosis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719282/
https://www.ncbi.nlm.nih.gov/pubmed/31497638
http://dx.doi.org/10.1016/j.dadm.2019.06.002

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719282/
https://www.ncbi.nlm.nih.gov/pubmed/31497638
http://dx.doi.org/10.1016/j.dadm.2019.06.002

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