Next-Generation Preventive Dentistry: Integrating Generative AI and Multimodal Algorithms into Clinical Workflows

Artificial intelligence (AI) and multimodal computational models are driving a paradigm shift in preventive dentistry by enhancing diagnostic precision, treatment planning, and patient engagement. Recent advances in generative AI, deep learning, and data fusion allow the simultaneous interpretation of radiographs, intraoral scans, and other diagnostic inputs, providing unprecedented opportunities for early disease detection and more targeted interventions. These tools are transforming the clinical workflow from reactive management of dental disease to proactive prevention and precision treatment, reducing procedural inefficiencies and improving patient outcomes. However, despite these advances, translational gaps remain regarding data privacy, model validation across diverse populations, and the readiness of dental professionals to adopt and implement such technologies. Addressing these challenges is essential for responsible AI integration in everyday practice.This Research Topic aims to investigate how generative AI and multimodal algorithmic systems can be effectively integrated into preventive and restorative dental workflows. It seeks to explore predictive and prescriptive analytic frameworks capable of improving diagnostic accuracy, forecasting treatment outcomes, and facilitating personalized care. The Research Topic also invites studies on the synergistic combination of AI tools with CAD/CAM technology to refine prosthetic design and orthodontic treatment planning. Furthermore, it encourages critical discussion of regulatory, educational, and ethical considerations to ensure that technological innovation supports clinical quality, transparency, and patient safety. Through this collection, the objective is to bridge the gap between algorithmic potential and practical clinical adoption.The scope of this Research Topic covers the implementation of AI‑based and multimodal computational tools in all areas of preventive dentistry, including diagnostics, clinical planning, and patient interaction, while excluding purely theoretical models without clinical relevance. To gather further insights into the integration of generative AI in dental medicine, we welcome articles addressing, but not limited to, the following themes:- Automated periodontal and peri‑implant analysis, diagnosis, and interpretation- Quantitative performance metrics and benchmarking of dental AI systems- Generative AI for restorative and orthodontic CAD/CAM design- Predictive analytics for individualized oral disease prevention- Multimodal data fusion and image analysis for early lesion detection- Ethical, legal, and data governance frameworks in dental AI applications- Workforce training and curricular redesign for AI‑ready clinical practiceWe encourage the submission of original research articles, clinical studies, methods papers, and comprehensive reviews that evaluate in silico, in vitro, or in vivo models illustrating the latest advances in algorithmic dentistry and their implications for the next generation of preventive dental care. Topic editors: Gustavo Fernandes, Rodrigo Resende Source: https://www.frontiersin.org/research-topics/84040/next-generation-preventive-dentistry-integrating-generative-ai-and-multimodal-algorithms-into-clinical-workflows