Examining Factors for Anxiety and Depression Prediction

Mental health conditions, such as anxiety and depression, are a significant public concern that can have impacts on an individual's quality of life, relationships, overall well-being. In recent years, data science machine learning techniques emerged important tools for early detection mental issues. This research aims at understanding the factors leading to depression implement predictive modelling improving accuracy efficiency diagnoses. Tabular DNN outperformed ANN other classifiers by approximately 30%. Overall, our findings suggest deep tabular models potential improve efficiency. Thereby helping in diagnoses so accessible convenient support individuals need context this work