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Abstract
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Introduction
Mental disorders are the main cause of mortality and morbidity worldwide. Deep learning offers a considerable promise for mental health diagnosis and risk assessment. The current study considered the potential application of deep learning methods in mental disorders.
Method
Four databases were reviewed between 2000 and February 2023, based on the PRISMA methodology. A total of 1339 papers was recognized and screened for their relevance to the use of deep learning algorithms in mental disease; 85 pertinent studies were identified and categorized based on several dimensions, such as subspecialty, deep learning methods, data sources, study limitations, and future directions.
Result
The obtained result revealed that deep learning in mental health is vastly used for depression and mood recognition analysis. The Convolutional Neural Network (CNN) is a prominent method applied in selected studies.
Conclusion
The results of this study may motivate further research on the use of deep learning in mental disorders and future directions for this promising technology.
Language: en |