Study of Web Based Mental Health Applications

Abstract

This paper examines the role of artificial intelligence (AI) in mental health platforms, addressing the increasing demand for innovative solutions in mental healthcare. Traditional diagnostic methods are often subjective, and early detection of mental health disorders like depression, anxiety, and ADHD remains challenging. AI, through machine learning, natural language processing, and wearable sensor data, offers new opportunities for creating digital phenotypes and enhancing diagnostic accuracy. Studies show that AI-driven platforms can analyze large datasets from electronic health records and real-time monitoring tools, providing early warnings and personalized care. AI models have demonstrated promise in identifying patterns that predict mental health conditions, improving intervention timing and outcomes. While AI holds great potential for transforming mental healthcare, ethical considerations, such as data privacy, transparency, and the need for clinically validated tools, remain essential challenges. As AI continues to advance, integrating these technologies responsibly will be crucial for improving access, reliability, and personalization in mental health interventions.