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The Algorithmic Divide: A Systematic Review on AI-Driven Racial Disparities in Healthcare

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An Ethical Perspective on the Democratization of Mental Health With Generative AI

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Behavioral health and generative AI: a perspective on future of therapies and patient care

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Equity in Digital Mental Health Interventions in the United States: Where to Next?

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Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach

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Large Language Models Versus Expert Clinicians in Crisis Prediction Among Telemental Health Patients: Comparative Study

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Explainable artificial intelligence systems for predicting mental health problems in autistics

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MENTAL HEALTH AND DIGITAL TECHNOLOGY: A PUBLIC HEALTH REVIEW OF CURRENT TRENDS AND RESPONSES

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Fusing Machine Learning and AI to Create a Framework for Employee Well-Being in the Era of Industry 5.0

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Opening the Black Box of Family-Based Treatments: An Artificial Intelligence Framework to Examine Therapeutic Alliance and Therapist Empathy

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The State of Digital Biomarkers in Mental Health

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An Engineering View on Emotions and Speech: From Analysis and Predictive Models to Responsible Human-Centered Applications

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Artificial Intelligence Models to Predict Disability for Mental Health Disorders

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Artificial Intelligence in Science and Society: The Vision of USERN

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The Impact of YouTube on Loneliness and Mental Health

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Medical Robotics and AI-Assisted Diagnostics Challenges for Smart Sustainable Healthcare

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Era of Generalist Conversational Artificial Intelligence to Support Public Health Communications

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Deep Learning Approaches to Natural Language Processing for Digital Twins of Patients in Psychiatry and Neurological Rehabilitation

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Eyes in the Sky

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Addressing the Flexible Use of Cognitive Flexibility Constructs: Toward a Multifaceted Approach

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Examining Ethical and Social Implications of Digital Mental Health Technologies Through Expert Interviews and Sociotechnical Systems Theory

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Navigating and Addressing Public Concerns in AI: Insights From Social Media Analytics and Delphi

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Using artificial intelligence to address mental health inequalities: co-creating machine learning algorithms with key stakeholders and citizen engagement

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Social Work Educators Innovating With Generative AI: An Exploratory Study

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Using machine learning to increase access to and engagement with trauma‐focused interventions for posttraumatic stress disorder

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Artificial Intelligence–Based Mobile Phone Apps for Child Mental Health: Comprehensive Review and Content Analysis

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Is there a tension between AI safety and AI welfare?

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From Stigma to Acceptance: Ethical Implications of Anthropomorphic Design in Healthcare Chatbots

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A Systematic Review on Mental Health Chatbots: Trends, Design Principles, Evaluation Methods, and Future Research Agenda

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An Ethical Perspective on The Democratization of Mental Health with Generative Artificial Intelligence (Preprint)Preprint

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Using deep learning-based artificial intelligence electronic images in improving middle school teachers’ literacy

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Enhancing ethical codes with artificial intelligence governance – a growing necessity for the adoption of generative AI in counselling

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A critical inquiry into the personal and societal perils of Artificial Intelligence

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Technology-enhanced practice competencies: scoping review and novel model development

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Artificial Intelligence for Mental Health Monitoring: A Solution for Digital Behavioral Health Care and Education—An Umbrella Review

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Use of Generative AIs in the Digital Communication and Marketing Sector in Spain

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Sustainability of AI-Assisted Mental Health Intervention: A Review of the Literature from 2020–2025

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Beyond clinical observations: a scoping review of AI-detectable observable cues in borderline personality disorder

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A Deep Learning Model for Psychological Support in Student Entrepreneurship

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AI-Driven Tools for Detecting and Monitoring Mental Health Conditions Though Behaviour Patterns

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Thinking Critically About Algorithms for Automated Detection of Behavior: 11 Guidelines for Social and Behavioral Scientists

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Developing personalized algorithms for sensing mental health symptoms in daily life

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Mental Health Disorders Due to Gut Microbiome Alteration and NLRP3 Inflammasome Activation After Spinal Cord Injury: Molecular Mechanisms, Promising Treatments, and Aids from Artificial Intelligence

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"I spent 14 hours debugging just one assignment": Toward Computer-Mediated Personal Informatics for Computer Science Student Mental Health

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Emotionally Intelligent AI

Wu, S. L., & Amini, M. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-5837-5.ch002 · Cited by 6 · see citing works

Comparing Generative Artificial Intelligence and Mental Health Professionals for Clinical Decision-Making With Trauma-Exposed Populations: Vignette-Based Experimental Study

Wislocki, K. E., Sami, S., Liberzon, G., & Zalta, A. K. (2025) · JMIR Mental Health · doi:10.2196/80801 · Cited by 6 · see citing works

AI and Personalised Grading Criteria

Ahmed, S., Zaki, A., & Bentley, Y. N. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-2145-4.ch004 · Cited by 6 · see citing works

Designing Human-Centric AI Mental Health Chatbots: A Case Study of Two Apps

Lee, K. S., Yeung, J., Kurniawati, A., & Chou, D. T. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-1747-0_36 · Cited by 7 · see citing works

A fair and interpretable deep learning approach for healthcare access prediction in underserved communities

Saxena, A., Sharma, S., Johari, P. K., Pandey, A., & Kumar, S. (2025) · Discover Artificial Intelligence · doi:10.1007/s44163-025-00425-3 · Cited by 6 · see citing works

AI Integration in Behavioral Healthcare: A Practical Framework for Clinicians

Sadeh‐Sharvit, S., & Hollon, S. D. (2025) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-025-00532-z · Cited by 7 · see citing works

Promoting Equity in AI-Driven Mental Health Care for Marginalized Populations

Tawiah, N. A., & Monestime, J. P. (2024) · Proceedings of the AAAI Symposium Series · doi:10.1609/aaaiss.v4i1.31810 · Cited by 5 · see citing works

Bridging fair-aware artificial intelligence and co-creation for equitable mental healthcare

Timmons, A. C., Duong, J. B., Walters, S. N., Carta, K. E., Jumonville, G. A., Carrasco, A. S., Romero, D., Ahle, M. W., Comer, J. S., Khurd, I. P., et al. (2025) · Nature Reviews Psychology · doi:10.1038/s44159-025-00491-5 · Cited by 6 · see citing works

Exploring the Bias Identification and Measuring Mechanisms in Mental Health Analysis

Choudhary, R., Kumar, G., & Saha, R. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-23219-9_20

Building Trust in AI-Driven Mental Health Tools

Goel, P. K., Yadav, S. P., & Verma, S. (2025) · IGI Global eBooks · doi:10.4018/979-8-3693-4203-9.ch004 · Cited by 1 · see citing works

Biased Bots: An Empirical Demonstration of How AI Bias Could Compromise Mental HealthcarePreprint

Timmons, A. C., Feng, K., Duong, J. B., Carta, K. E., Walters, S., Jumonville, G. A., Carrasco, A. S., Freitag, G. F., Romero, D., Margolin, G., et al. (2024) · doi:10.31234/osf.io/7t98e · Cited by 2 · see citing works