Publication

Abstract : In today's fast-paced society, psychological health issues such as anxiety, depression, and stress have become prevalent among the general population. Researchers have explored the use of machine learning algorithms to predict the likelihood of depression in individuals. As datasets related to depression become more abundant and machine learning technology advances, there is an opportunity to develop intelligent systems capable of identifying symptoms of depression in written material. By applying natural language processing and machine learning algorithms to analyze written text, such as social media posts, emails, and chat messages, researchers can potentially identify patterns and linguistic cues associated with depression. These patterns may include changes in word usage, tone, and sentiment. The dataset consists of text-based questions on this information channel. At present, machine learning techniques are highly effective for analyzing data and identifying problems. Researchers have conducted comparisons of the accuracy achieved by different machine learning algorithms using the complete set of attributes as well as a subset of selected attributes. In summary, while the potential for AI to aid in mental health diagnosis and treatment is exciting, it's important to proceed with care and consideration for the complexities of the field and the needs of patients.