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Título
Application of machine learning techniques to help in the feature selection related to hospital readmissions of suicidal behavior
Autor
Año del Documento
2022
Editorial
Springer
Descripción
Producción Científica
Documento Fuente
International Journal of Mental Health and Addiction, 2022.
Resumen
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
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
Propietario de los Derechos
© 2022 The Author(s)
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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