Data-driven categorization of postoperative delirium symptoms using unsupervised machine learning

BACKGROUND: Phenotyping analysis that includes time course is useful for understanding the mechanisms and clinical management of postoperative delirium. However, postoperative delirium has not been fully phenotyped. Hypothesis-free categorization of heterogeneous symptoms may be useful for understan...

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Detalles Bibliográficos
Autores principales: Sri-iesaranusorn, Panyawut, Sadahiro, Ryoichi, Murakami, Syo, Wada, Saho, Shimizu, Ken, Yoshida, Teruhiko, Aoki, Kazunori, Uezono, Yasuhito, Matsuoka, Hiromichi, Ikeda, Kazushi, Yoshimoto, Junichiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Psychiatry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333495/
https://www.ncbi.nlm.nih.gov/pubmed/37441147
http://dx.doi.org/10.3389/fpsyt.2023.1205605

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333495/
https://www.ncbi.nlm.nih.gov/pubmed/37441147
http://dx.doi.org/10.3389/fpsyt.2023.1205605

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