DIAGNOSIS AND MONITORING OF MENTAL DISORDERS ASSISTED BY A MOBILE APPLICATION WITH IA IN THE CASE OF UNIVERSITY STUDENTS.

• DOI: https://doi.org/10.22533/at.ed.3174252421107

• Palavras-chave: Aprendizaje máquina, internet de las cosas médicas, herramientas tecnológicas, sensores portátiles, escalas trastornos mental.

• Keywords: Machine learning, internet of medical things, technological tools, wearable sensors, mental disorder scales.

• Abstract:

  Globally, it is estimated that approximately 254 million students are enrolled in universities (UNESCO, 2024). (UNESCO, 2024)of which 5.2 million are in Mexico (SEP, 2023). (SEP, 2023). Of these, 36.9% present some type of emotional disorder, such as stress, depression or anxiety, which are some of the main mental health problems among adolescents (INEGI, 2024). (INEGI, 2024).. At the Tecnológico Nacional de México/Instituto Tecnológico de Tuxtla Gutiérrez, in the Computer Systems Engineering program, 44% of students drop out of the program (Autores,2024). Previous studies in this institution indicate that these emotional disorders affect academic performance and contribute significantly to school dropout. (Ortiz, Basave, Sánchez, & Ortiz, 2021).. However, mental disorders are difficult to diagnose due to the similarity of their symptoms, which are often common among various mental illnesses. In this paper, we explore different metrics based on questionnaires and biological indicators, which serve as input data for machine learning methods. These methods allow identifying, diagnosing, monitoring and predicting the main mental disorders in university students, and their integration into technological tools such as mobile applications, chatbots, recognition and monitoring systems.