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Gema Castillo-Sánchez

Dados Biográficos

ID7841943
NOMEGema Castillo-Sánchez
PRENOMESGema
SOBRENOMECastillo-Sánchez
ASSINATURACASTILLO-SÁNCHEZ G
AFILIAÇÕESUniversidad de Valladolid
ORCID0000-0002-8247-604X
VERIFICADOSim
TOTAL DE OBRAS3
TOTAL DE CITAÇÕES0
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2021
ANO MAIS RECENTE DE PUBLICAÇÃO2024
ÍNDICE H0
  • A Digital Mental Health Approach for Supporting Suicide Prevention

    Open Access•Gema Castillo-Sánchez, José Miguel Toribio-Guzmán et al.•ARTICLE•International Journal of Mental…•2024

  • Application of Machine Learning Techniques to Help in the Feature Selection Related to Hospital Readmissions of Suicidal Behavior

    Open Access•Gema Castillo-Sánchez, Mario Jojoa et al.•ARTICLE•International Journal of Mental…•2022

    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 readm…

  • Sentiment Analysis Techniques Applied to Raw-Text Data from a Csq-8 Questionnaire about Mindfulness in Times of Covid-19 to Improve Strategy Generation

    Open Access•Mario Jojoa, Gema Castillo-Sánchez et al.•ARTICLE•International Journal of…•2021

    The use of artificial intelligence in health care has grown quickly. In this sense, we present our work related to the application of Natural Language Processing techniques, as a tool to analyze the sentiment perception of users who answered two questions from the CSQ-8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in…

Sem obras proeminentes nesta página.

  • Sentiment Analysis Techniques Applied to Raw-Text Data from a Csq-8 Questionnaire about Mindfulness in Times of Covid-19 to Improve Strategy Generation

    Open Access•Mario Jojoa, Gema Castillo-Sánchez et al.•ARTICLE•International Journal of…•2021

    The use of artificial intelligence in health care has grown quickly. In this sense, we present our work related to the application of Natural Language Processing techniques, as a tool to analyze the sentiment perception of users who answered two questions from the CSQ-8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in…

  • Application of Machine Learning Techniques to Help in the Feature Selection Related to Hospital Readmissions of Suicidal Behavior

    Open Access•Gema Castillo-Sánchez, Mario Jojoa et al.•ARTICLE•International Journal of Mental…•2022

    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 readm…

  • A Digital Mental Health Approach for Supporting Suicide Prevention

    Open Access•Gema Castillo-Sánchez, José Miguel Toribio-Guzmán et al.•ARTICLE•International Journal of Mental…•2024

Medicine (3 obras) · Psychology (3 obras) · Clinical Psychology (2 obras) · Clinical Psychology (2 obras) · Health psychology (2 obras) · Nursing (2 obras) · Poison control (2 obras) · Psychiatry (2 obras) · Public health (2 obras) · Suicide and Self-Harm Studies (2 obras)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae