ReviewDiagnostics (Basel, Switzerland)2025
Artificial Intelligence in Psychiatry: A Review of Biological and Behavioral Data Analyses.
Review in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
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
26 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence in mental health care: a scoping review of reviews.Frontiers in psychiatry · 2026Pooled it
- Multimodal observable cues in mood, anxiety, and borderline personality disorders: a review of reviews to inform explainable AI in mental health.Frontiers in artificial intelligence · 2025Pooled it
- Just a Minute: A Pupil-Based Machine Learning Approach to Depression Screening.Applied psychophysiology and biofeedback · 2026Article
- Development and validation of nomograms for predicting depression and suicidal ideation in stroke survivors: a community-based study.BMC psychiatry · 2026Article
- Toward a hybrid assessment framework for adolescent borderline personality disorder: a mini review of personality functioning, digital biomarkers, and AI-supported assessment.Frontiers in psychiatry · 2026Review
- Quantitative electroencephalography as a next-generation tool in neurodiagnostics: significance, clinical applications, and practical interpretative frameworks.Frontiers in neuroscience · 2026Review
- From synapse to system: mechanistic pathways of neural signaling dysfunction in psychiatric disorders.Frontiers in cell and developmental biology · 2026Review
- Ethical evaluation of AI-supported mental health applications.Frontiers in psychiatry · 2026Article
- A Competing-Risk Nomogram for in-Hospital Non-Suicidal Self-Injury Recurrence Using Inflammatory and Clinical Predictors.Risk management and healthcare policy · 2026Article
- Suicide probability among physicians: an explainable machine learning analysis of depression, burnout, anxiety, and coping styles.Frontiers in medicine · 2026Article
- Applications of Artificial Intelligence Technologies in Nursing for Noncommunicable Chronic Diseases: A Scoping Review.Journal of nursing management · 2026Article
- Specialised Competencies and Artificial Intelligence in Perioperative Care: Contributions Toward Safer Practice.Healthcare (Basel, Switzerland) · 2025Review
- AI Applications in Depression Detection and Diagnosis: Bibliometric and Visual Analysis of Trends and Future Directions.JMIR mental health · 2025Article
- Self-AttentionNeXt: Exploring schizophrenic optical coherence tomography image detection investigations.World journal of psychiatry · 2025Article
- Intelligence Architectures and Machine Learning Applications in Contemporary Spine Care.Bioengineering (Basel, Switzerland) · 2025Review
- Examining the biological causes of eating disorders to inform treatment strategies.Nature reviews. Neuroscience · 2025Review
- Brain Tumors, AI and Psychiatry: Predicting Tumor-Associated Psychiatric Syndromes with Machine Learning and Biomarkers.International journal of molecular sciences · 2025Review
- An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders.BMC psychiatry · 2025Article
- Leveraging AI-Driven Neuroimaging Biomarkers for Early Detection and Social Function Prediction in Autism Spectrum Disorders: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- The use of deep learning and artificial intelligence-based digital technologies in art education.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has emerged as a transformative force in psychiatry, improving diagnostic precision, treatment personalization, and early intervention through advanced data analysis techniques. This review explores recent advancements in AI applications within psychiatry, focusing on EEG and ECG data analysis, speech analysis, natural language processing (NLP), blood biomarker integration, and social media data utilization. EEG-based models have significantly enhanced the detection of disorders such as depression and schizophrenia through spectral and connectivity analyses. ECG-based approaches have provided insights into emotional regulation and stress-related conditions using heart rate variability. Speech analysis frameworks, leveraging large language models (LLMs), have improved the detection of cognitive impairments and psychiatric symptoms through nuanced linguistic feature extraction. Meanwhile, blood biomarker analyses have deepened our understanding of the molecular underpinnings of mental health disorders, and social media analytics have demonstrated the potential for real-time mental health surveillance. Despite these advancements, challenges such as data heterogeneity, interpretability, and ethical considerations remain barriers to widespread clinical adoption. Future research must prioritize the development of explainable AI models, regulatory compliance, and the integration of diverse datasets to maximize the impact of AI in psychiatric care.
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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.