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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/55566

    Título
    Application of machine learning techniques to help in the feature selection related to hospital readmissions of suicidal behavior
    Autor
    Castillo Sánchez, Gema Anabel
    Jojoa Acosta, Mario
    Garcia Zapirain, Begonya
    Torre Díez, Isabel de laAutoridad UVA
    Franco Martín, Manuel Ángel
    Año del Documento
    2022
    Editorial
    Springer
    Descripción
    Producción Científica
    Documento Fuente
    International Journal of Mental Health and Addiction, 2022.
    Abstract
    Suicide was the main source of death from external causes in Spain in 2020, with 3,941 cases. The importance of identifying those mental disorders that influenced hospital readmissions will allow us to manage the health care of suicidal behavior. The feature selection of each hospital in this region was carried out by applying Machine learning (ML) and traditional statistical methods. The results of the characteristics that best explain the readmissions of each hospital after assessment by the psychiatry specialist are presented. Adjustment disorder, alcohol abuse, depressive syndrome, personality disorder, and dysthymic disorder were selected for this region. The most influential methods or characteristics associated with suicide were benzodiazepine poisoning, suicidal ideation, medication poisoning, antipsychotic poisoning, and suicide and/or self-harm by jumping. Suicidal behavior is a concern in our society, so the results are relevant for hospital management and decision-making for its prevention.
    Materias Unesco
    33 Ciencias Tecnológicas
    32 Ciencias Médicas
    Palabras Clave
    Machine learning
    Readmissions
    Mental disorder
    Suicide prevention
    Hospital
    ISSN
    1557-1874
    Revisión por pares
    SI
    DOI
    10.1007/s11469-022-00868-0
    Patrocinador
    Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLE
    Version del Editor
    https://link.springer.com/article/10.1007/s11469-022-00868-0
    Propietario de los Derechos
    © 2022 The Author(s)
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/55566
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    • DEP71 - Artículos de revista [358]
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    Universidad de Valladolid

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