Abstract

THERAPY AND MANAGEMENT FOR DEPRESSION AND ANXIETY USING ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML)

Teasha Chakraborty*, Rahit Paul, Suman Dey, Souvik Dey, Md. Asif, Vaibhav Raj and Rajesh Ghosh

ABSTRACT

The Artificial Intelligence (AI) and Machine Learning (ML) fields provide us with the knowledge of brain function, improving early identification and treat various neurological disorders. The importance of AI/ML in brain-computer interface is to improve techniques for gathering knowledge, evaluating, and preventing neurological diseases. ML has been used in clinical studies in psychiatry, mental disorder detection, disease prognosis, treatment, and patient support. However, the integration of AI with human intellect requires gradual progress. While enhanced medicine offers individualized care, the treatment of neurological diseases remains under the human intellect's authority. The SCL-90-R is a psychiatric health assessment tool with 90 questions, used to assess ten major mental illnesses. However, it is lengthy and time-consuming. Other instruments, such as the BSI-18,SCL-14, and SCL-25, have been developed to diagnose specific conditions. Audio CNN models have shown better accuracy, whereas a study conducted at a community-based clinic in America discovered that AI-derived insights helped quicken patients' responses to behavioral therapy. These findings suggest that AI can help improve treatment outcomes and patient satisfaction. Wearable AI was used for two-thirds of the research, with heart rate variability being a key biosignal for mental stress. Python and scikit-learn were used for machine learning modeling in a study. The ensemble model, consisting of base and averaging layers, demonstrated superiority over single-model solutions. Chatbots, driven by AI, have shown promise in various industries, providing psychological support and guidance for individuals struggling with mental health issues. The mobile chatbot psychologist uses AIML to understand user input and offer tailored interventions, addressing mental wellness care disparities. This review offers a thorough analysis of the upcoming future of using Artificial Intelligence (AI) and Machine Learning (ML) in cognitive and behavioral aspects.

Keywords: Artificial Intelligence, Machine Learning, Depression, Neurological disease, Neuro-psychology, SCL-90-R.