ArticleHealth science reports2026
AI in Mental Health: Transforming Diagnosis and Management of Depression and Anxiety.
Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Mental health disorders, especially depression and anxiety, are major contributors to the global disease burden. Traditional psychiatric methods can be time-consuming and often struggle with accurate diagnosis and effective treatment. Artificial intelligence (AI) has the potential to improve diagnostic precision and streamline the management of mental health issues. Methodology: This review investigates AI's role in addressing mental health challenges, with a focus on anxiety and depression. Relevant literature was sourced from Medline, Google Scholar, and PubMed, using keywords like "artificial intelligence," "mental health," "depression," and "anxiety," emphasizing studies involving Asian populations. The search included English-language articles, which were screened based on titles and abstracts. Discussion: AI applications in psychiatry, including chatbots and wearable devices, enable early detection and individualized care. Machine learning and deep learning models that use data from sources such as social media and sensors assist in diagnosing and monitoring mental health conditions. Although these tools provide valuable support, ethical concerns related to privacy, algorithmic bias, and limitations in detecting suicidal ideation need to be addressed. Conclusion: AI shows promise in transforming mental health care by increasing diagnostic speed, accuracy, and accessibility. Despite existing challenges, particularly around ethical considerations and acceptance in older populations, further research and careful regulation could allow AI to complement human-centered psychiatric care. Future studies should work to maximize the benefits of AI while preserving the critical human connection in mental health services.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.