Machine Learning Approaches to Identify Factors Associated with Women's Vasomotor Symptoms Using General Hospital Data

BACKGROUND: To analyze the factors associated with women's vasomotor symptoms (VMS) using machine learning. METHODS: Data on 3,298 women, aged 40–80 years, who attended their general health check-up from January 2010 to December 2012 were obtained from Korea University Anam Hospital in Seoul, K...

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Detalles Bibliográficos
Autores principales: Ryu, Ki-Jin, Yi, Kyong Wook, Kim, Yong Jin, Shin, Jung Ho, Hur, Jun Young, Kim, Tak, Seo, Jong Bae, Lee, Kwang-Sig, Park, Hyuntae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Academy of Medical Sciences 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093602/
https://www.ncbi.nlm.nih.gov/pubmed/33942581
http://dx.doi.org/10.3346/jkms.2021.36.e122

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093602/
https://www.ncbi.nlm.nih.gov/pubmed/33942581
http://dx.doi.org/10.3346/jkms.2021.36.e122

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