Advances in Machine Learning and Explainable Artificial Intelligence for Depression Prediction

There is a growing interest in applying AI technology the field of mental health, particularly as an alternative to complement limitations human analysis, judgment, and accessibility health assessments treatments. The current treatment service faces gap which individuals who need help are not receiving it due negative perceptions treatment, lack professional manpower, physical limitations. To overcome these difficulties, there for new approach, being explored potential solution. Explainable artificial intelligence (X-AI) with both accuracy interpretability can improve expert decision-making, increase services, solve psychological problems high-risk groups depression. In this review, we examine use X-AI As result reviewing 6 studies that used discriminate depression, various algorithms such SHAP (SHapley Additive exPlanations) Local Interpretable Model-Agnostic Explanation (LIME) were predicting psychiatry, crucial ensure prediction justifications clear transparent. Therefore, ensuring models will be important future research.