Depression is a prevalent and severe mental health disorder that impacts
millions globally, often manifesting through varied and subtle language
expressions in text. Early detection is critical to enabling timely intervention and
improving patient outcomes. This study presents a deep learning model
specifically designed for the classification of mental health texts, focusing on
depression detection
