Arquitectura de PLN aplicada al contexto de la salud mental NLP architecture applied to the context of mental health

Abstract

At a global level, the situation caused by COVID-19 has created a worrying and discouraging reality, especially for governments, especially for the most vulnerable populations due to the fact that they do not know how to eradicate the pandemic, many have not been able to overcome the challenges mainly emerging from an infectious disease with implications for physical health and which has also profoundly affected people's mental health and well-being. Mental health affectations are problems that affect all of us at some point in our lives, either due to experiences we have experienced or even biological factors. Paying attention and providing the necessary support at an early stage is the key to preventing more severe effects. The discipline of natural language processing (NLP) is a sub-area of artificial intelligence (AI) that studies the interactions between computers and the language that humans speak. This research proposes the design and implementation of a comprehensive architecture based on AI, machine learning (ML) and PLN components, which will allow us to detect and analyze behavior patterns in people and generate possible early diagnoses of mental health diseases.