Effectiveness of artificial intelligence in detecting and managing depressive disorders: Systematic review

This study underscores the importance of exploring AI's creative applications in treating depressive disorders to revolutionize mental health care. Through innovative integration of AI technologies, the research confirms their positive effects on preventing, diagnosing, and treating depression....

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Veröffentlicht in:Journal of affective disorders 2024-09, Vol.361, p.445-456
Hauptverfasser: Park, Yoonseo, Park, Sewon, Lee, Munjae
Format: Artikel
Sprache:eng
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Zusammenfassung:This study underscores the importance of exploring AI's creative applications in treating depressive disorders to revolutionize mental health care. Through innovative integration of AI technologies, the research confirms their positive effects on preventing, diagnosing, and treating depression. The systematic review establishes an evidence base for AI in depression management, offering directions for effective interventions. This systematic literature review investigates the effectiveness of AI in depression management by analyzing studies from January 1, 2017, to May 31, 2022. Utilizing search engines like IEEE Xplore, PubMed, and Web of Science, the review focused on keywords such as Depression/Mental Health, Machine Learning/Artificial Intelligence, and Prediction/Diagnosis. The analysis of 95 documents involved classification based on use, data type, and algorithm type. The study revealed that AI in depression management excelled in accuracy, particularly in monitoring and prediction. Biomarker-derived data demonstrated the highest accuracy, with the CNN algorithm proving most effective. The findings affirm the therapeutic benefits of AI, including treatment, detection, and disease prediction, highlighting its potential in analyzing monitored data for depression management. This study exclusively examined the application of AI in individuals with depressive disorders. Interpretation should be cautious due to the limited scope of subjects to this specific population. To introduce digital healthcare and therapies for ongoing depression management, it's crucial to present empirical evidence on the medical fee payment system, safety, and efficacy. These findings support enhanced medical accessibility through digital healthcare, offering personalized disease management for patients seeking non-face-to-face treatment. •Many people with depression suffer from physical symptoms such as headaches and insomnia, which often prevent them from receiving timely treatment.•Recently, the use of artificial intelligence (AI) for the treatment and management of depression has been gaining momentum as a potential solution to this problem.•Through these various comparative analyzes such as comparative analysis by prediction, comparative analysis by data, and comparative analysis by algorithm, it is possible to identify the strengths and weaknesses of artificial intelligence technology used in the treatment of depressive disorders in providing accuracy•This baseline data wi
ISSN:0165-0327
1573-2517
1573-2517
DOI:10.1016/j.jad.2024.06.035