Identifying and evaluating clinical subtypes of Alzheimer’s disease in care electronic health records using unsupervised machine learning

BACKGROUND: Alzheimer’s disease (AD) is a highly heterogeneous disease with diverse trajectories and outcomes observed in clinical populations. Understanding this heterogeneity can enable better treatment, prognosis and disease management. Studies to date have mainly used imaging or cognition data a...

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Detalles Bibliográficos
Autores principales: Alexander, Nonie, Alexander, Daniel C., Barkhof, Frederik, Denaxas, Spiros
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8653614/
https://www.ncbi.nlm.nih.gov/pubmed/34879829
http://dx.doi.org/10.1186/s12911-021-01693-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8653614/
https://www.ncbi.nlm.nih.gov/pubmed/34879829
http://dx.doi.org/10.1186/s12911-021-01693-6

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