RT info:eu-repo/semantics/article
T1 Application of machine learning techniques to help in the feature selection related to hospital readmissions of suicidal behavior
A1 Castillo Sánchez, Gema Anabel
A1 Jojoa Acosta, Mario
A1 Garcia Zapirain, Begonya
A1 Torre Díez, Isabel de la
A1 Franco Martín, Manuel Ángel
K1 Machine learning
K1 Readmissions
K1 Mental disorder
K1 Suicide prevention
K1 Hospital
K1 33 Ciencias Tecnológicas
K1 32 Ciencias Médicas
AB 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.
PB Springer
SN 1557-1874
YR 2022
FD 2022
LK https://uvadoc.uva.es/handle/10324/55566
UL https://uvadoc.uva.es/handle/10324/55566
LA eng
NO International Journal of Mental Health and Addiction, 2022.
NO Producción Científica
DS UVaDOC
RD 01-may-2024