Ethical, Regulatory, and Health Economic Considerations of Artificial Intelligence in Restorative Dentistry
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AuthorsAbstractThe purpose of this scoping review was to map and synthesize the ethical, regulatory and health economic issues related to the use of AI in restorative dentistry, focusing on caries detection, assessment of restorations, CAD/CAM workflow, crown design, shade selection, prediction of restoration longevity, and endodontic-restorative decision-making. A scoping review using a narrative synthesis approach was undertaken. There were 125 records found through electronic and supplementary searches. 103 records were screened by title and abstract after the removal of duplicates 22. From these, 45 records were excluded and 58 full text articles were evaluated for eligibility. A total of 38 sources were used in the final synthesis after excluding 20 full-text articles. The results were grouped thematically as clinical applications, ethical considerations, regulatory considerations, health economic implications and evidence gaps. The most common AI applications were caries detection, radiographic interpretation, CAD/CAM workflows, crown design, prosthodontic planning, restoration survival prediction and shade selection. Ethical issues were related to privacy, informed consent, algorithmic bias, explainability, automation bias, and accountability. Themes of regulation were intended use, validation, Software as a Medical Device, post-market monitoring and liability. Direct health economic evidence was scarce with no study included in the review having conducted a full cost-effectiveness, reimbursement or budget impact analysis. While AI holds potential in restorative dentistry, its ethical use must be safeguarded by proper regulations, oversight, economic analysis, and practical validation. AI should be used to assist, not supplant, restorative dentists' clinical judgment. Keywords: Artificial intelligence; Restorative dentistry; Ethics; Health economics. 1. Introduction The use of AI in digital dentistry is rapidly growing and has been incur porated in the interpretation of images, diagnosis, treatment planning, prediction of outcomes, and workflow automation. In particular, AI holds great promise in the realm of restorative dentistry, where many clinical decisions are dependent on diagnostic accuracy, radiographic interpretation, material selection, restoration design, and prognosis. The use of AI in restorative dentistry has been reviewed recently, and includes caries detection, evaluation of restorations, CAD/CAM workflows, crown design, tooth shade selection, prosthodontic planning, and prediction of the longevity of restorations [1,2]. Other studies on a wider scale have also revealed the use of AI in various dental specialties such as diagnosis, radiology, prosthodontics, restorative dentistry, endodontics and digital treatment planning [3,4]. Restorative dentistry is a very critical field for the implementation of AI as AI-driven decisions can be related to caries monitoring vs restoration, to repair vs replace a restoration, to the design of a crown,. or to the of a restoration. Revilla-León et al. carried out a prognosis systematic review of AI applications in restorative •••••••••••••••••••••••••••••••• ejprd.org- Published by Riset Publishing Services LLC.
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