Machine learning based hierarchical classification of frontotemporal dementia and Alzheimer's disease

BACKGROUND: In a clinical setting, an individual subject classification model rather than a group analysis would be more informative. Specifically, the subtlety of cortical atrophy in some frontotemporal dementia (FTD) patients and overlapping patterns of atrophy among three FTD clinical syndromes i...

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Detalles Bibliográficos
Autores principales: Kim, Jun Pyo, Kim, Jeonghun, Park, Yu Hyun, Park, Seong Beom, Lee, Jin San, Yoo, Sole, Kim, Eun-Joo, Kim, Hee Jin, Na, Duk L., Brown, Jesse A., Lockhart, Samuel N., Seo, Sang Won, Seong, Joon-Kyung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6458431/
https://www.ncbi.nlm.nih.gov/pubmed/30981204
http://dx.doi.org/10.1016/j.nicl.2019.101811

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6458431/
https://www.ncbi.nlm.nih.gov/pubmed/30981204
http://dx.doi.org/10.1016/j.nicl.2019.101811

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