AIMC Topic: Mental Disorders

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Nanopsychiatry: Advancing psychiatric diagnosis and monitoring through nanotechnology-based detection.

Clinica chimica acta; international journal of clinical chemistry
Nanopsychiatry, operating at the nanoscale, leverages engineered nanomaterials and nanodevices to revolutionize psychiatric diagnostics and therapeutics. This review systematically analyzes the implementation of advanced nanomaterials, including quan...

An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study.

JMIR medical informatics
BACKGROUND: Machine learning (ML) systems in health care have the potential to enhance decision-making but often fail to address critical issues such as prediction explainability, confidence, and robustness in a context-based and easily interpretable...

Psychedelic Drugs in Mental Disorders: Current Clinical Scope and Deep Learning-Based Advanced Perspectives.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mental disorders are a representative type of brain disorder, including anxiety, major depressive depression (MDD), and autism spectrum disorder (ASD), that are caused by multiple etiologies, including genetic heterogeneity, epigenetic dysregulation,...

Generalizability of clinical prediction models in mental health.

Molecular psychiatry
Concerns about the generalizability of machine learning models in mental health arise, partly due to sampling effects and data disparities between research cohorts and real-world populations. We aimed to investigate whether a machine learning model t...

The impact of AI-driven sentiment analysis on patient outcomes in psychiatric care: A narrative review.

Asian journal of psychiatry
This article addresses the pressing question of how advanced analytical tools, specifically artificial intelligence (AI)-driven sentiment analysis, can be effectively integrated into psychiatric care to enhance patient outcomes. Utilizing specific se...

AI-based personalized real-time risk prediction for behavioral management in psychiatric wards using multimodal data.

International journal of medical informatics
BACKGROUND: Suicide is a major global health issue, with approximately 700,000 deaths annually (WHO). In psychiatric wards, managing harmful behaviors such as suicide, self-harm, and aggression is essential to ensure patient and staff safety. However...

Individual and integrated indexes of inflammation predicting the risks of mental disorders - statistical analysis and artificial neural network.

BMC psychiatry
OBJECTIVE: The prevalence of mental illness in Taiwan increased. Identifying and mitigating risk factors for mental illness is essential. Inflammation may be a risk factor for mental illness; however, the predictive power of inflammation test values ...

Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets.

Neural networks : the official journal of the International Neural Network Society
Objective classification biomarkers that are developed using resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for psychiatric disorders. Unfortunately, no widely accepted biomar...

Psychiatric Genomics 2025: State of the Art and the Path Forward.

The Psychiatric clinics of North America
Psychiatric genetics has evolved from candidate-gene studies to whole-genome sequencing efforts. With hundreds of disease-associated loci now identified, functional interpretation of the associated loci becomes the critical next step toward translati...

Building Trust with AI: How Essential is Validating AI Models in the Therapeutic Triad of Therapist, Patient, and Artificial Third? Comment on What is the Current and Future Status of Digital Mental Health Interventions?

The Spanish journal of psychology
Since the publication of "What is the Current and Future Status of Digital Mental Health Interventions?" the exponential growth and widespread adoption of ChatGPT have underscored the importance of reassessing its utility in digital mental health int...