Harnessing the Power of NLP for Mental Health Diagnosis and Treatment

Global public health concerns about mental health continue to grow. The increasing use of social media has stimulated interest in the early detection of mental diseases through the evaluation of user-generated content. Mental health issues, such as eating disorders (ED), depression, and anxiety, are common when this state of well-being is disrupted. One in eight people in the world received such a diagnosis in 2019, and anxiety and depression were the most common. There are two major objectives: First, NLP could proficiently identify patterns of mental conditions or emotional distress in the message of the user over time and, Secondly, LLMs deliver quality information towards mental health specialists. In testing these predictions, fundamental challenges of the domain are addressed: it explores the possibility to recognize emotional disease symptoms from texts and potential in chatbots ability to collect professional-grade data of users' correspondence.