Técnicas de Machine Learning aplicadas al consumo de sustancias psicoactivas ilícitas: Un mapeo sistémico

Autores/as

  • Jefferson Eduardo Campo Yule Universidad del Cauca. Popayán, (Colombia)
  • Danny alberto Díaz Mage Universidad del Cauca. Popayán, (Colombia)
  • Hugo Armando Ordoñez Universidad del Cauca, Popayán, (Colombia)

DOI:

https://doi.org/10.17981/ingecuc.19.2.2023.08

Palabras clave:

Machine learning, sustancias psicoactivas ilegales,, drogas ilegales, modelos predictivos, nuevas sustancias psicoactivas ilegales

Resumen

Introducción— El consumo de sustancias psicoactivas ilícitas es una problemática que se vive a diario, donde personas de diferentes edades se han visto implicadas, resaltando que muchas de estas sustancias generan trastornos tales como, por ejemplo: la Marihuana o cannabis: su consumo afecta la función cerebral de manera directa, y particularmente las partes del cerebro responsables de la memoria, el aprendizaje, la atención, la toma de decisiones. El Bazuco: es una sustancia tóxica, cuyos principales riesgos de consumirla se reflejan en el deterioro neurológico y en el organismo, y es muy rápida su disolución en el torrente sanguíneo, aspecto que hace que sea muy adictiva. La Cocaína: su consumo afecta directamente el sistema nervioso y el resto del organismo de forma inmediata, en estas afectaciones se encuentran vasoconstricción, midriasis, hipertermia, taquicardia e hipertensión. La Heroína: es una sustancia altamente adictiva, inicialmente, sus efectos son muy placenteros, lo que propicia una conducta de consumo continuada y repetitiva, además, produce sensaciones de sequedad en la boca, enrojecimiento y acaloramiento de la piel, pesadez en brazos y piernas, náuseas y vómitos, comezón intensa y enturbiamiento de las facultades mentales. 

Objetivo— Esta problemática es algo que resalta mucho y de gran impacto en los jóvenes de acuerdo al contexto en el que se encuentren ya que hoy en dia hay mucha facilidad para obtener este tipo de sustancias, por ende, se han planteado una serie de trabajos que abordan desde la inteligencia artificial esa problemática. 

Metodología— El presente estudio realiza una revisión de 50 publicaciones relacionadas con el uso de métodos y técnicas de ML aplicadas al consumo de sustancias psicoactivas ilícitas. 

Resultados— De las publicaciones incluidas se hallaron temáticas en común por lo que se hace un resumen de los artículos seleccionados por cada temática y se describen brevemente los métodos adoptados, así como también una comparativa entre ellos, anotando los métodos usados, sus resultados y demás factores importantes de la aplicación o modelo en distintas áreas y se concluye con una serie de propuestas sobre las líneas que a futuro podrían encaminar la investigación en este campo.

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Citas

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Publicado

2023-07-10

Cómo citar

Campo Yule, J. E., Díaz Mage, D. alberto ., & Ordoñez, H. A. (2023). Técnicas de Machine Learning aplicadas al consumo de sustancias psicoactivas ilícitas: Un mapeo sistémico. Inge Cuc, 19(2), 97–. https://doi.org/10.17981/ingecuc.19.2.2023.08

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