Psychiatry

Latest AI and machine learning research in psychiatry for healthcare professionals.

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Modeling Higher-Order Brain Interactions via a Multi-View Information Bottleneck Framework for fMRI-based Psychiatric Diagnosis

Resting-state functional magnetic resonance imaging (fMRI) has emerged as a cornerstone for psychiat...

Evaluating Large Language Models for Transparent Quality-of-Care Measurement in Children with ADHD

ImportanceGuideline-concordant care for young children with attention-deficit/hyperactivity disorder...

Sustaining Control and Agency Under Threat: Computational Pathways to Persistence and Escape

Adaptive behavior requires deciding when to persist and when to disengage under uncertainty and part...

IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures

Ask a frontier model how to taper six milligrams of alprazolam (psychiatrist retired, ten days of pi...

Unlocking Multi-Site Clinical Data: A Federated Approach to Privacy-First Child Autism Behavior Analysis

Automated recognition of autistic behaviors in children is essential for early intervention and obje...

How and why does deep ensemble coupled with transfer learning increase performance in bipolar disorder and schizophrenia classification?

Transfer learning (TL) and deep ensemble learning (DE) have recently been shown to outperform simple...

Grading of Erythema and Visual Attributes in Atopic Dermatitis across Diverse Skin Tones Using a Vision AI Pipeline

Background: Atopic dermatitis (AD) is a prevalent chronic inflammatory skin disease associated with ...

Developing a Tiered Machine Learning Alert System for Real-Time Suicide Risk Detection in a Digital Mental Health Setting

The goal of this work was to leverage a large corpus of text based psychotherapy data to create nove...

Elder-Sim: A Psychometrically Validated Platform for Personality-Stable Elderly Digital Twins

Background: LLMs enable patient-facing conversational agents, creating a pathway toward digital twin...

MAMGL: A memory-augmented meta-graph learning framework for adolescent major depression disorder diagnosis

Adolescent major depressive disorder (AMDD) is a prevalent and heterogeneous psychiatric condition t...

D-GATNet: Interpretable Temporal Graph Attention Learning for ADHD Identification Using Dynamic Functional Connectivity

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder whose neu...

DuSCN-FusionNet: An Interpretable Dual-Channel Structural Covariance Fusion Framework for ADHD Classification Using Structural MRI

Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental condition; ...

Identification of Suicide-Related Subgroups Using Latent Class Analysis: Complementary Insights to Explainable AI-Based Classification

Purpose: Suicide and self-harm are major public health concerns characterized by substantial clinica...

Knowledge-Guided Retrieval-Augmented Generation for Zero-Shot Psychiatric Data: Privacy Preserving Synthetic Data Generation

AI systems in healthcare research have shown potential to increase patient throughput and assist cli...

Social Determinants of Health and Chronic Disease Risk Prediction in the All of Us Research Program

Social determinants of health (SDoH), the social, economic, and environmental conditions shaping hea...

Aggregate benchmark scores obscure patient safety implications of errors across frontier language models

Frontier language models are widely used for health-related queries, yet aggregate benchmark scores ...

Causal differential expression analysis under unmeasured confounders with causarray

Advances in single-cell sequencing and CRISPR technologies have enabled detailed case-control compar...

Beyond AI Psychosis and Sycophancy: Structural Drift as a System-Level Safety Failure

Background: Conversational AI safety systems are primarily evaluated using message-level content mon...

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