Machine-Learning-Based Diagnosis of Mental Health Issues

Preventing common mental diseases like anxiety as well as depression have grown into a worldwide priority. Therefore, there is a need to develop effective solutions to such issues. For serving such needs, machine learning methods have been integrated into medical facilities for the identification as well as forecasting of treatment results for illnesses related to mental well-being. The previous literature focuses on such mental well-being like suicidal thoughts, stress, anxiety, depression, and bipolar disorder along with minor aspects like mixed reality, emotional states (moods), mental health education, pharmacogenomics, precision psychiatry, chronic disease contracting, body mass index, and wearable sensors were chosen and subsequently classified into the various grounds of comparison for making the survey more comprehensive. Finally, the future directives for the research on mental health goodness are presented.