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Subcategories: Addictions Anxiety & Stress Bipolar Disorder Depression DSM-5 Eating Disorders Schizophrenia

Showing 3823-3843 of 5,977 articles

Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach.

Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and c...

Jun 2025 40262465

Assessing bias in AI-driven psychiatric recommendations: A comparative cross-sectional study of chatbot-classified and CANMAT 2023 guideline for adjunctive therapy in difficult-to-treat depression.

The integration of chatbots into psychiatry introduces a novel approach to support clinical decision...

Jun 2025 40267866

Exploring pesticide risk in autism via integrative machine learning and network toxicology.

Autism Spectrum Disorder (ASD) is a prevalent neurodevelopmental condition influenced by both geneti...

Jun 2025 40280042

AnnaAgent: Dynamic Evolution Agent System with Multi-Session Memory for Realistic Seeker Simulation

Constrained by the cost and ethical concerns of involving real seekers in AI-driven mental health,...

May 2025 http://arxiv.org/abs/2506.00551v1

Unsupervised Evolutionary Cell Type Matching via Entropy-Minimized Optimal Transport

Identifying evolutionary correspondences between cell types across species is a fundamental challe...

May 2025 http://arxiv.org/abs/2505.24759v1

Beyond FACS: Data-driven Facial Expression Dictionaries, with Application to Predicting Autism

The Facial Action Coding System (FACS) has been used by numerous studies to investigate the links ...

May 2025 http://arxiv.org/abs/2505.24679v1

Artificial intelligence-assisted chatbot: impact on breastfeeding outcomes and maternal anxiety.

BACKGROUND: Artificial intelligence (AI) is increasingly used in healthcare interventions to provide...

May 2025 40448061

Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study.

BACKGROUND: Conventional approaches for major depressive disorder (MDD) screening rely on two effect...

May 2025 40446148

3DGEER: Exact and Efficient Volumetric Rendering with 3D Gaussians

3D Gaussian Splatting (3DGS) marks a significant milestone in balancing the quality and efficiency...

May 2025 http://arxiv.org/abs/2505.24053v1

ConversAR: Exploring Embodied LLM-Powered Group Conversations in Augmented Reality for Second Language Learners

Group conversations are valuable for second language (L2) learners as they provide opportunities t...

May 2025 http://arxiv.org/abs/2505.24000v1

Speech as a Multimodal Digital Phenotype for Multi-Task LLM-based Mental Health Prediction

Speech is a noninvasive digital phenotype that can offer valuable insights into mental health cond...

May 2025 http://arxiv.org/abs/2505.23822v1

Predicting Human Depression with Hybrid Data Acquisition utilizing Physical Activity Sensing and Social Media Feeds

Mental disorders including depression, anxiety, and other neurological disorders pose a significan...

May 2025 http://arxiv.org/abs/2505.22779v1

A highly scalable deep learning language model for common risks prediction among psychiatric inpatients.

BACKGROUND: There is a lack of studies exploring the performance of Transformers-based language mode...

May 2025 40437564

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts

Despite rapid advances in large language models (LLMs), their integration with traditional supervi...

May 2025 http://arxiv.org/abs/2505.21324v1

SELF-PERCEPT: Introspection Improves Large Language Models' Detection of Multi-Person Mental Manipulation in Conversations

Mental manipulation is a subtle yet pervasive form of abuse in interpersonal communication, making...

May 2025 http://arxiv.org/abs/2505.20679v1

Browse Categories

Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach.

Assessing bias in AI-driven psychiatric recommendations: A comparative cross-sectional study of chatbot-classified and CANMAT 2023 guideline for adjunctive therapy in difficult-to-treat depression.

Exploring pesticide risk in autism via integrative machine learning and network toxicology.

AnnaAgent: Dynamic Evolution Agent System with Multi-Session Memory for Realistic Seeker Simulation

Unsupervised Evolutionary Cell Type Matching via Entropy-Minimized Optimal Transport

Beyond FACS: Data-driven Facial Expression Dictionaries, with Application to Predicting Autism

Artificial intelligence-assisted chatbot: impact on breastfeeding outcomes and maternal anxiety.

Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study.

3DGEER: Exact and Efficient Volumetric Rendering with 3D Gaussians

ConversAR: Exploring Embodied LLM-Powered Group Conversations in Augmented Reality for Second Language Learners

Speech as a Multimodal Digital Phenotype for Multi-Task LLM-based Mental Health Prediction

Predicting Human Depression with Hybrid Data Acquisition utilizing Physical Activity Sensing and Social Media Feeds

A highly scalable deep learning language model for common risks prediction among psychiatric inpatients.

Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts

SELF-PERCEPT: Introspection Improves Large Language Models' Detection of Multi-Person Mental Manipulation in Conversations

Reasoning Is Not All You Need: Examining LLMs for Multi-Turn Mental Health Conversations

Does Rationale Quality Matter? Enhancing Mental Disorder Detection via Selective Reasoning Distillation

Performance of machine learning models for predicting high-severity symptoms in multiple sclerosis.

Literature review on assistive technologies for people with Parkinson's disease

Multi-Modal Spectral Parametrization Method (MMSPM) for analyzing EEG activity with distinct scaling regimes

Multi-Modal Spectral Parametrization Method (MMSPM) for analyzing EEG activity with distinct scaling regimes

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