ReviewAnnals of medicine and surgery (2012)2025
Artificial intelligence in mental health: integrating opportunities and challenges of multimodal deep learning for mental disorder prevention and treatment.
Review in Annals of medicine and surgery (2012), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- A bibliometric analysis of research on the application of just-in-time adaptive interventions in mental health.Medicine · 2026Review
- Effects of crocin on anxiety, depression, and hippocampal BDNF expression in streptozotocin-induced diabetic rats.Annals of medicine and surgery (2012) · 2026Article
- Trusting and staying with AI doctors: cognitive and emotional pathways driving continuance intention toward AI healthcare chatbots.Frontiers in public health · 2026Article
- Multimodal EEG and explainable machine learning characterize neuroticism-related neurodynamic heterogeneity in mild cognitive impairment during visuospatial working memory.Frontiers in aging neuroscience · 2026Article
- The role of artistic creativity in predicting difficulties in emotion regulation and reducing social anxiety: insights from a cross-sectional analysis.Annals of medicine and surgery (2012) · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI), through multimodal deep learning and predictive analytics, holds transformative potential in the prevention and treatment of mental disorders. This study explores the opportunities and challenges of these technologies. Objective: To present a conceptual framework for the responsible application of AI in mental health care. Methods: This integrative review analyzed selected sources from Google Scholar up to June 2025. Both qualitative and quantitative analyses were conducted to identify opportunities and challenges. Results: Key opportunities include early detection, personalized treatment, and enhanced access to mental health services. Major challenges involve ethical concerns, algorithmic bias, and data quality issues. Conclusion: AI can revolutionize mental health care, but it requires standardization and regulatory oversight. Future research should focus on addressing ethical dilemmas and improving data quality.
Indexed as
Identifiers
What OpenQuestion holds
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.