Abstract: The present research aims to develop an application that allows the early and timely detection of signs of problems in the mental health of citizens. Agile methodology was used, with its SCRUM framework developing its four steps. In addition, technological tools such as artificial intelligence, mobile appli-cations, social networks and the python programming language were used. Also using SQL Server, Android Studio and the Marvel applications, the latter for the design of the prototypes, through the method of sentiment analysis and machine learning, in order to create a mobile application that is as accurate as possible in its results. For this, several types of algorithm were evaluated, managing to select the most appropriate one since it works based on information collected through the social networks Facebook and Twitter. The result that was obtained was the application that uses machine learning to prevent and take care of mental health in Peru, thus benefiting the citizens of society.

Edwin Kcomt Ponce, Melissa Flores Cruz and Laberiano Andrade-Arenas, “Machine Learning Applied to Prevention and Mental Health Care in Peru” International Journal of Advanced Computer Science and Applications(IJACSA), 13(1), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130196

@article{Ponce2022,
title = {Machine Learning Applied to Prevention and Mental Health Care in Peru},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130196},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130196},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {1},
author = {Edwin Kcomt Ponce and Melissa Flores Cruz and Laberiano Andrade-Arenas}
}