{"id":11445,"date":"2024-12-23T12:49:35","date_gmt":"2024-12-23T12:49:35","guid":{"rendered":"https:\/\/congressaio.it\/daia\/"},"modified":"2025-06-03T14:56:01","modified_gmt":"2025-06-03T14:56:01","slug":"daia","status":"publish","type":"page","link":"https:\/\/congressaio.it\/en\/daia\/","title":{"rendered":"DAIA"},"content":{"rendered":"

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Dental Artificial Intelligence
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\n\t\t\t\t\t\t\t\t\t\t\t\t10 Ada cerp\/PACE credits<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/h2>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t
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Moderator: <\/strong>Enrico Lai<\/strong><\/a><\/p>\n

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\t\t\t\t14.50 - 14.55 | Introduction<\/span>\n\t\t\t\t<\/h4>\t\t<\/div>\n\t\t[vc_column_text css=””]<\/p>\n

Enrico Lai<\/a><\/p>\n

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\t\t\t\t14.55 - 15.25 | The Evolution of Artificial Intelligence in Dentistry<\/span>\n\t\t\t\t<\/h4>\t\t<\/div>\n\t\t[vc_column_text css=””]Ameed Khalid Abdul-Hamid<\/a> <\/strong>[\/vc_column_text]\t\t\t
\n\t\t[vc_column_text css=””]The integration of Artificial Intelligence (AI) into dentistry marks a transformative era in dental practice and research. This lecture traces the historical development of AI in dentistry, beginning with the early algorithmic concepts in ancient Mesopotamia. The Mesopotamians, known for their advancements in mathematics and early computational methods, laid the foundational principles that would eventually influence modern algorithmic thinking.<\/p>\n

From these ancient beginnings, the lecture will explore the journey of AI in dentistry, from its conceptual inception in the mid-20th century to its current applications and future potential. Initially, AI’s role in dentistry was limited to theoretical explorations and rudimentary applications. However, the advent of advanced computational power, big data, and sophisticated algorithms in the late 20th and early 21st centuries catalyzed significant advancements.<\/p>\n

Key milestones include the introduction of computerized tomography (CT) in the 1970s, which revolutionized dental imaging, and the subsequent development of machine learning and neural networks that enhanced diagnostic accuracy and treatment planning. The lecture will highlight pivotal moments such as the adoption of AI in radiographic analysis, the use of AI-driven tools in orthodontics, periodontics, prosthodontics, and the emergence of AI in patient management and personalized treatment plans.<\/p>\n

A special focus will be given to AI’s role in oral pathology, where AI algorithms have significantly improved the detection and diagnosis of oral diseases. By analyzing vast datasets of histopathological images, AI systems can identify patterns and anomalies with high precision, aiding pathologists in early and accurate diagnosis of conditions such as oral cancer and other pathologies.<\/p>\n

Furthermore, the lecture will discuss the symbiotic relationship between evidence-based dentistry and AI, emphasizing how AI complements clinical expertise to improve patient outcomes. Ethical considerations, challenges, and the future trajectory of AI in dentistry will also be explored, providing a comprehensive overview of this dynamic field.)[\/vc_column_text]\t\t\t

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\t\t\t\t15.25 -15.55 | A Guide to AI Standards in Dentistry<\/span>\n\t\t\t\t<\/h4>\t\t<\/div>\n\t\t[vc_column_text css=””]Ken Aschheim<\/strong><\/a>[\/vc_column_text]\t\t\t
\n\t\t[vc_column_text css=””]This presentation explores the evolving landscape of artificial intelligence (AI) standards and their implications for dentistry. It underscores the growing need for scientific rigor, oversight, and accountability in AI and how the DAIA can be pivotal in developing standards to ensure consistency, reliability, and adherence to best practices. It will begin with the historical contributions of national standards organizations such as DIN (Germany), JISC (Japan), and ANSI (USA), highlighting their collaboration with ISO in creating technical guidelines that facilitate advancements recognized globally by government agencies. The focus will be on the processes involved in developing standards, including procedural and essential requirements, consensus-building, and the necessary resources for effective development. Additionally, it will address the importance of interdisciplinary collaboration and the integration of various factors in standard development. A key emphasis will be placed on the ANSI and ISO processes, establishing guidelines that promote transparency, quality control, and interoperability, essential for developing meaningful AI standards. Finally, the presentation will conclude with how organizations such as DAIA can influence these standards by engaging with national development organizations, such as the ADA Standards Program.[\/vc_column_text]\t\t\t
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\t\t\t\t15.55 - 16.25 | Artificial Intelligence and Dentronics in Laser Dentistry: Revolutionizing Diagnosis and Treatment<\/span>\n\t\t\t\t<\/h4>\t\t<\/div>\n\t\t[vc_column_text css=””]Sonia Regina Bordin Aykroyd<\/strong> <\/a>[\/vc_column_text]\t\t\t
\n\t\t[vc_column_text css=””]Lasers are utilized in various diagnostic and treatment systems, ranging from oral cancer and caries detection devices to imaging systems like digital scanners. They also serve as therapeutic tools, from thermal ablative devices to non-thermal photonic systems used for healing and pain management.<\/p>\n

The integration of Artificial Intelligence (AI) in laser dentistry is transforming clinical practice by enhancing diagnostic accuracy, optimizing treatment planning, and improving patient outcomes. This presentation discusses the current applications of AI in laser-assisted procedures and the potential for future advancements. AI systems are utilized to interpret diagnostic data from imaging technologies, guiding laser treatments with unparalleled precision. These systems facilitate early detection of dental diseases, including oral cancer and caries, and ensure patient-specific treatment plans, minimizing the risk of human error.<\/p>\n

AI-driven lasers in minimally invasive procedures have the potential to provide enhanced precision in cavity preparations and hard tissue ablation, thereby reducing tissue thermal damage and accelerating recovery. Additionally, the development of femtosecond laser technology, integrated with AI, offers improved outcomes in restorative dentistry by minimizing thermal and mechanical damage. The application of robotics, such as the “LaserBot” for tooth crown preparation, represents a significant advancement in the field, showcasing the potential for AI-assisted robotics to increase efficiency and precision.<\/p>\n

Another groundbreaking development is the emergence of Catalytic Antimicrobial Robots (CARs), which offer a novel approach to eradicating bacterial biofilms in hard-to-reach dental areas. CARs, driven by AI, combine catalytic and magnetic functionalities to degrade biofilm structures, eliminate bacteria, and remove debris, providing a promising solution for combating infections in dental treatments.<\/p>\n

However, the successful implementation of AI in laser dentistry is met with challenges, including data privacy concerns, algorithmic bias, and the need for robust regulatory frameworks. As the field evolves, overcoming these barriers will be critical to fully realizing the potential of AI in enhancing dental care. Future trends include the integration of AI with robotic-driven systems, augmented reality (AR), and virtual reality (VR) for improved clinical training, treatment planning, and precision-based interventions.<\/p>\n

In conclusion, AI is poised to play a transformative role in laser dentistry, improving diagnostic accuracy, treatment outcomes, and clinical workflows, while presenting opportunities for future innovations in preventive and restorative dental care.<\/p>\n

Teaching Objectives:<\/strong><\/p>\n