Artificial intelligence (AI) is rapidly transforming oral healthcare through applications in diagnostic imaging, risk prediction, treatment planning, and patient management. However, despite AI's potential to enhance clinical decision-making and streamline clinical workflows, significant concerns exist regarding equity, accessibility, and patient-centered implementation. Critical challenges include ensuring AI tools are validated across varied clinical settings and populations, addressing algorithmic transparency to maintain clinician trust and autonomy, and preventing technology-driven widening of the oral health gap between well-resourced and underserved communities. A human-centered approach to AI in oral health prioritizes the needs, values, and contexts of all patients and practitioners, emphasizing transparency, explainability, and meaningful stakeholder engagement throughout the AI lifecycle. This Research Topic explores how AI can be developed, validated, and implemented to advance equitable oral healthcare rather than widen existing disparities.

This Research Topic aims to bridge the gap between AI innovation and patient-centered, equitable implementation in oral healthcare. While recent advances have demonstrated AI's capability in automated diagnosis, predictive analytics, and personalized treatment planning, translating these technologies into real-world practice that benefits all populations remains a significant challenge. We seek to explore how AI can be thoughtfully integrated into oral healthcare to benefit patients, practitioners, and healthcare systems. This Research Topic welcomes contributions across the full spectrum of AI applications in oral health. We are particularly interested in work that addresses human-centered AI development and validation, implementation science and real-world deployment strategies, algorithmic transparency and clinical interpretability, applications in resource-limited or underserved settings, patient and provider perspectives on AI integration, and ethical frameworks for responsible AI use in oral healthcare.

This Research Topic seeks contributions that advance the understanding, development, and implementation of AI in oral healthcare with emphasis on human-centered and equitable approaches. We welcome the following themes:

• AI Development and Validation: Novel AI algorithms and models for oral health applications, including diagnostic systems, predictive analytics, and clinical decision support tools.

• Implementation Science and Real-World Deployment: Research on strategies for integrating AI into clinical workflows.

• Human-Centered Design and Usability: Studies examining user experience, clinician-AI interaction, and design approaches that prioritize patient and provider needs.

• Equity and Access: Investigations of AI applications in resource-limited or underserved settings, studies addressing potential biases in AI systems, and strategies for ensuring equitable distribution of AI benefits across different populations and practice environments.

• Algorithmic Transparency and Interpretability: Research on explainable AI methods, clinical interpretability of AI outputs, and approaches to building trust and understanding among clinicians and patients.

• Ethical, Legal, and Social Implications: Analyses of ethical frameworks for AI use in oral health, data privacy considerations, regulatory challenges, and patient perspectives on AI integration.

Are you interested in contributing a manuscript to this Research Topic?

Reimagining Artificial Intelligence in Oral Health: Human-Centered Approaches for Equitable Healthcare