A Practical Approach to Predicting Depression: Verbal and Non-Verbal Insights with Machine Learning

Abstract

While global standards have been established for diagnosing depression, the reliance on expert judgement and observation remains a challenge. This study delves into a potential approach of efficient data collection to increase the practicability of machine learning models in accurately predicting depression based on a comprehensive analysis of verbal and non-verbal cues exhibited by individuals.