Summary of the Veterans Health Administration's First International Symposium on Artificial Intelligence in Dentistry

The Veterans Health Administration's First International Symposium on Artificial Intelligence in Dentistry, held virtually on October 11, 2024, marked a step toward improving oral health care for veterans through the adoption of cutting-edge artificial intelligence (AI) technologies. AI offers the potential to transform dental diagnostics, treatment planning, and care delivery; however, its clinical application in dentistry remains limited. The symposium addressed this gap by means of highlighting innovations and implementation strategies to help clinicians prepare for the technological changes reshaping oral health care.

The authors summarized presentations and panel discussions from the symposium, encompassing developments in AI-assisted cariology, maxillofacial radiology, diagnostic and presurgical planning, clinical workflows, remote monitoring, and the ethical and regulatory landscape. The review is based on content submitted by the symposium's presenters, reflecting their research, operational experience, and emerging innovations.

The presentations established that AI technologies can standardize diagnostics, reduce interoperator variability, and enhance clinical decision making through predictive analytics, digital simulations, and multimodal data integration. AI applications exhibited high specificity in detecting pathologies, improved early intervention capabilities, and optimized treatment planning. Key findings emphasized the value of responsible AI adoption within institutional settings, such as the US Department of Veterans Affairs, supported by means of clinician engagement, regulatory guidance, and ethical oversight.

Integrating AI into dental practice can improve diagnostic accuracy, streamline administrative processes, and enhance access to care. These tools offer substantial benefits for large health care systems, such as the Veterans Health Administration, including greater efficiency, personalization of treatment, and improved outcomes, particularly in underserved or resource-limited environments.