El aprendizaje automático y su uso en la detección del trastorno de la depresión.

Depression disorder is a silent but deadly condition, which millions of people suffer from, and its consequences can be devastating, especially because those who suffer from it rarely seek professional help, aggravating the symptoms over time. Furthermore, one of the biggest problems that this condition encompasses is the lack of early detection. The emergence of new technologies is emerging as a possible solution to this problem, specifically the use of machine learning applied in the detection of depression disorder can be the tool that helps overcome the lack of access to a diagnosis and allow many people to have timely help, so this research work aims to analyze studies carried out where this technology is applied and be able to compare the results with each other, managing to find out which of the machine learning algorithms is the most efficient and demonstrate that its use can achieve equal or more precise results than the methods. traditional ones used in the detection of the disorder. In this research, it was possible to obtain information from several algorithms in which machine learning models were applied for the detection of the disorder using different data sources for their training, with the sociodemographic data set being the most used by researchers for the detection of depression.

• Auteur principal: Montiel Olvera, Fernando Stiven (author)
• Format: bachelorThesis
• Publié: 2025
• Sujets: Aprendizaje automático; Trastorno; Depresión; Algoritmo; Sistema de Información
• Accès en ligne: http://dspace.utb.edu.ec/handle/49000/17825