Simulation of suicide tendency by using machine learning

Hugo D. Calderon-Vilca; William I. Wun-Rafael; Roberto Miranda-Loarte

doi:10.1109/SCCC.2017.8405128

Simulation of suicide tendency by using machine learning

Hugo D. Calderon-Vilca, William I. Wun-Rafael, Roberto Miranda-Loarte

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

15 Citas (Scopus)

Resumen

Suicide is one of the most distinguished causes of death on the news worldwide. There are several factors and variables that can lead a person to commit this act, for example, stress, self-esteem, depression, among others. The causes and profiles of suicide cases are not revealed in detail by the competent institutions. We propose a simulation with a systematically generated dataset; such data reflect the adolescent population with suicidal tendency in Peru. We will evaluate three algorithms of supervised machine learning as a result of the algorithm C4.5 which is based on the trees to classify in a better way the suicidal tendency of adolescents. We finally propose a desktop tool that determines the suicidal tendency level of the adolescent.

Idioma original	Inglés
Título de la publicación alojada	2017 36th International Conference of the Chilean Computer Science Society, SCCC 2017
Editorial	IEEE Computer Society
Páginas	1-6
Número de páginas	6
ISBN (versión digital)	9781538634837
DOI	https://doi.org/10.1109/SCCC.2017.8405128
Estado	Publicada - 2 jul. 2017
Publicado de forma externa	Sí
Evento	36th International Conference of the Chilean Computer Science Society, SCCC 2017 - Arica, Chile Duración: 16 oct. 2017 → 20 oct. 2017

Serie de la publicación

Nombre	Proceedings - International Conference of the Chilean Computer Science Society, SCCC
Volumen	2017-October
ISSN (versión impresa)	1522-4902

Conferencia

Conferencia	36th International Conference of the Chilean Computer Science Society, SCCC 2017
País/Territorio	Chile
Ciudad	Arica
Período	16/10/17 → 20/10/17

Nota bibliográfica

Publisher Copyright:
© 2017 IEEE.

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10.1109/SCCC.2017.8405128

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Calderon-Vilca, H. D., Wun-Rafael, W. I., & Miranda-Loarte, R. (2017). Simulation of suicide tendency by using machine learning. En 2017 36th International Conference of the Chilean Computer Science Society, SCCC 2017 (pp. 1-6). (Proceedings - International Conference of the Chilean Computer Science Society, SCCC; Vol. 2017-October). IEEE Computer Society. https://doi.org/10.1109/SCCC.2017.8405128

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title = "Simulation of suicide tendency by using machine learning",

abstract = "Suicide is one of the most distinguished causes of death on the news worldwide. There are several factors and variables that can lead a person to commit this act, for example, stress, self-esteem, depression, among others. The causes and profiles of suicide cases are not revealed in detail by the competent institutions. We propose a simulation with a systematically generated dataset; such data reflect the adolescent population with suicidal tendency in Peru. We will evaluate three algorithms of supervised machine learning as a result of the algorithm C4.5 which is based on the trees to classify in a better way the suicidal tendency of adolescents. We finally propose a desktop tool that determines the suicidal tendency level of the adolescent.",

keywords = "Suicide tendency, classification, machine learning, prevention, suicide, suicide attempt, suicide risk",

author = "Calderon-Vilca, {Hugo D.} and Wun-Rafael, {William I.} and Roberto Miranda-Loarte",

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Calderon-Vilca, HD, Wun-Rafael, WI & Miranda-Loarte, R 2017, Simulation of suicide tendency by using machine learning. En 2017 36th International Conference of the Chilean Computer Science Society, SCCC 2017. Proceedings - International Conference of the Chilean Computer Science Society, SCCC, vol. 2017-October, IEEE Computer Society, pp. 1-6, 36th International Conference of the Chilean Computer Science Society, SCCC 2017, Arica, Chile, 16/10/17. https://doi.org/10.1109/SCCC.2017.8405128

Simulation of suicide tendency by using machine learning. / Calderon-Vilca, Hugo D.; Wun-Rafael, William I.; Miranda-Loarte, Roberto.
2017 36th International Conference of the Chilean Computer Science Society, SCCC 2017. IEEE Computer Society, 2017. p. 1-6 (Proceedings - International Conference of the Chilean Computer Science Society, SCCC; Vol. 2017-October).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AB - Suicide is one of the most distinguished causes of death on the news worldwide. There are several factors and variables that can lead a person to commit this act, for example, stress, self-esteem, depression, among others. The causes and profiles of suicide cases are not revealed in detail by the competent institutions. We propose a simulation with a systematically generated dataset; such data reflect the adolescent population with suicidal tendency in Peru. We will evaluate three algorithms of supervised machine learning as a result of the algorithm C4.5 which is based on the trees to classify in a better way the suicidal tendency of adolescents. We finally propose a desktop tool that determines the suicidal tendency level of the adolescent.

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KW - machine learning

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KW - suicide attempt

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Simulation of suicide tendency by using machine learning

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