Machine learning-based prediction of post-stroke cognitive status using electroencephalography-derived brain network attributes

OBJECTIVES: More than half of patients with acute ischemic stroke develop post-stroke cognitive impairment (PSCI), a significant barrier to future neurological recovery. Thus, predicting cognitive trajectories post-AIS is crucial. Our primary objective is to determine whether brain network propertie...

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Detalles Bibliográficos
Autores principales: Lee, Minwoo, Hong, Yuseong, An, Sungsik, Park, Ukeob, Shin, Jaekang, Lee, Jeongjae, Oh, Mi Sun, Lee, Byung-Chul, Yu, Kyung-Ho, Lim, Jae-Sung, Kang, Seung Wan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Aging Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568623/
https://www.ncbi.nlm.nih.gov/pubmed/37842126
http://dx.doi.org/10.3389/fnagi.2023.1238274

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568623/
https://www.ncbi.nlm.nih.gov/pubmed/37842126
http://dx.doi.org/10.3389/fnagi.2023.1238274

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