A Survey: Performance-aware Depression Detection

Depression is the most common health problem in the world. According to the World Health Organization (WHO), more than 350 million people are affected by it. There are many causes of depression, like business down and down, social life, economic life, and relationships. Depression is one of the leading causes of mental illness in humans and also affects an individual's thoughts, behavior, emotions and well-being. This survey is useful to the clinical understanding of mental health for patients. The main goal of the survey was to study the different learning techniques to find out the research gap. In this survey we studied the different existing research work with their systems, and different types of datasets (Image data, Audio data and textual data). The final results are based on different parameters like accuracy, precision, and recall etc. This paper explores the learning techniques to learn the different learning techniques for the depression detection system.