TY - JOUR
KW - Addiction
KW - Artificial Intelligence
KW - Homelessness
KW - Psychoactive Substances
KW - Social Justice
AU - Hugo Ordoñez
AU - Ricardo Timarán-Pereira
AU - Juan-Sebastián González-Sanabria
AB - Introduction: Currently, homelessness should not be seen as just another problem, but as a reality of inequality and the absence of social justice. In this sense, homeless people are subjected to social disengagement, lack of job opportunities or the instability of these, insecurity circumstances, these aspects being one of the causes associated with the consumption or addiction to psychoactive substances. Data: To define the proposed approach, data from the Census of Street Inhabitants - CHC- 2021 of the National Administrative Department of Statistics (DANE), which contains 19,375 records and 25 columns, were used. Methodology: This article presents an artificial intelligence approach that implements a model based on machine learning algorithms for identifying addiction trends to psychoactive substances in street dwellers in Colombia. Conclusions: Based on the results obtained, it is evident that the approach can serve as a support for decision making by municipal administrations in the definition of social public policies for the street-dwelling population in Colombia.

IS - In press
M1 - In press
N2 - Introduction: Currently, homelessness should not be seen as just another problem, but as a reality of inequality and the absence of social justice. In this sense, homeless people are subjected to social disengagement, lack of job opportunities or the instability of these, insecurity circumstances, these aspects being one of the causes associated with the consumption or addiction to psychoactive substances. Data: To define the proposed approach, data from the Census of Street Inhabitants - CHC- 2021 of the National Administrative Department of Statistics (DANE), which contains 19,375 records and 25 columns, were used. Methodology: This article presents an artificial intelligence approach that implements a model based on machine learning algorithms for identifying addiction trends to psychoactive substances in street dwellers in Colombia. Conclusions: Based on the results obtained, it is evident that the approach can serve as a support for decision making by municipal administrations in the definition of social public policies for the street-dwelling population in Colombia.

PY - 9998
SE - 1
SP - 1
EP - 9
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - Trends in Addiction to Psychoactive Substances Among Homeless People in Colombia Using Artificial Intelligence
UR - https://www.ijimai.org/journal/sites/default/files/2024-02/ip2024_02_002.pdf
VL - In press
SN - 1989-1660
ER -