A Review of Machine Learning and Deep Learning Approaches on Mental Health Diagnosis

Iyortsuun, Ngumimi Karen; Kim, Soo-Hyung; Jhon, Min; Yang, Hyung-Jeong; Pant, Sudarshan

doi:10.3390/healthcare11030285

reviewHealthcareJan 17, 2023GOLD OA

A Review of Machine Learning and Deep Learning Approaches on Mental Health Diagnosis

NKNgumimi Karen Iyortsuun SKSoo-Hyung Kim MJMin Jhon HYHyung-Jeong Yang SPSudarshan Pant

Chonnam National University · Chonnam National University Hwasun Hospital

PubMed

Indexed incrossrefpubmed

Abstract

Combating mental illnesses such as depression and anxiety has become a global concern. As a result of the necessity for finding effective ways to battle these problems, machine learning approaches have been included in healthcare systems for the diagnosis and probable prediction of the treatment outcomes of mental health conditions. With the growing interest in machine and deep learning methods, analysis of existing work to guide future research directions is necessary. In this study, 33 articles on the diagnosis of schizophrenia, depression, anxiety, bipolar disorder, post-traumatic stress disorder (PTSD), anorexia nervosa, and attention deficit hyperactivity disorder (ADHD) were retrieved from various search…

Citation impact

259

total citations

FWCI: 80.52
Percentile: 100%
References: 79

Citations per year

Authors

5

Topics & keywords

Topics

Keywords

Anxiety
Mental health
Artificial intelligence
Machine learning
Deep learning
Bipolar disorder
Schizophrenia (object-oriented programming)
Psychiatry

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