Artificial intelligence and smile design: An e-Delphi consensus statement of ethical challenges.

PURPOSE: Smile design software increasingly relies on artificial intelligence (AI). However, using AI for smile design raises numerous technical and ethical concerns. This study aimed to evaluate these ethical issues. METHODS: An international consortium of experts specialized in AI, dentistry, and smile design was engaged to emulate and assess the ethical challenges raised by the use of AI for smile design. An e-Delphi protocol was used to seek the agreement of the ITU-WHO group on well-established ethical principles regarding the use of AI (wellness, respect for autonomy, privacy protection, solidarity, governance, equity, diversity, expertise/prudence, accountability/responsibility, sustainability, and transparency). Each principle included examples of ethical challenges that users might encounter when using AI for smile design. RESULTS: On the first round of the e-Delphi exercise, participants agreed that seven items should be considered in smile design (diversity, transparency, wellness, privacy protection, prudence, law and governance, and sustainable development), but the remaining four items (equity, accountability and responsibility, solidarity, and respect of autonomy) were rejected and had to be reformulated. After a second round, participants agreed to all items that should be considered while using AI for smile design. CONCLUSIONS: AI development and deployment for smile design should abide by the ethical principles of wellness, respect for autonomy, privacy protection, solidarity, governance, equity, diversity, expertise/prudence, accountability/responsibility, sustainability, and transparency.

Blended intensive programme's implementation in dental education: post-pandemic evolution of learning.

Blended Intensive Programmes (BIP's) represent a valuable tool for gathering knowledge and summarising the latest trends in medicine and dentistry. Blended education has been found, even before the COVID-19 pandemic, to increase the level of education and stimulate effective learning for postgraduate healthcare professionals. Interprofessional education is critical for preparing students to enter the health workforce, where teamwork and collaboration are important competencies. This article outlines the key points of the Blended Intensive Programme's implementation in dental education organised by Wroclaw Medical University in Poland. BIP involved professors from 12 universities or research institutions from Europe and South America and 28 participants from 8 countries. The course was taught remotely and in person. In addition, it included a visit to the university and practical classes with artificial simulation and practice in dentistry. A structured questionnaire enabled measuring the evaluation of students' perception of the COVID-19 education before and after the pandemic. The European Region Action Scheme for the Mobility of University Students (ERASMUS) was fundamental to carrying out the BIP with the participation of several countries, allowing the exchange of knowledge, assessing the impact of the pandemic on dental universities, and strengthening international collaborations and the future project of research, education and clinical assistance. We conclude that hybrid teaching programmes broaden the learning spectrum in dental studies by allowing transnational and interdisciplinary approaches that make students aware of the importance of their work within the framework of the general health approach, as this differs from country to country.

Ethical considerations on artificial intelligence in dentistry: A framework and checklist.

OBJECTIVE: Artificial Intelligence (AI) refers to the ability of machines to perform cognitive and intellectual human tasks. In dentistry, AI offers the potential to enhance diagnostic accuracy, improve patient outcomes and streamline workflows. The present study provides a framework and a checklist to evaluate AI applications in dentistry from this perspective. METHODS: Lending from existing guidance documents, an initial draft of the checklist and an explanatory paper were derived and discussed among the groups members. RESULTS: The checklist was consented to in an anonymous voting process by 29 Topic Group Dental Diagnostics and Digital Dentistry, ITU/WHO Focus Group AI on Health's members. Overall, 11 principles were identified (diversity, transparency, wellness, privacy protection, solidarity, equity, prudence, law and governance, sustainable development, accountability, and responsibility, respect of autonomy, decision-making). CONCLUSIONS: Providers, patients, researchers, industry, and other stakeholders should consider these principles when developing, implementing, or receiving AI applications in dentistry. CLINICAL SIGNIFICANCE: While AI has become increasingly commonplace in dentistry, there are ethical concerns around its usage, and users (providers, patients, and other stakeholders), as well as the industry should consider these when developing, implementing, or receiving AI applications based on comprehensive framework to address the associated ethical challenges.

Artificial intelligence for sustainable oral healthcare.

OBJECTIVES: Oral health is grounded in the United National (UN) 2030 Agenda for Sustainable Developement and its 17 Goals (SDGs), in particular SDG 3 (Ensure healthy lives and promote well-being for all at all ages). The World Health Organization (WHO) Global Strategy on Oral Health calls for prioritizing environmentally sustainable and less invasive oral health care, and planetary health. Artificial Intelligence (AI) has the potential to power the next generation of oral health services and care, however its relationship with the broader UN and WHO concepts of sustainability remains poorly defined and articulated. We review the double-edged relationships between AI and oral health, to suggest actions that promote a sustainable deployment of AI for oral health. DATA: Concepts regarding AI, sustainability and sustainable development were identified and defined. A review of several double-edged relationship between AI and SDGs were exposed for the field of Oral Health. SOURCES: Medline and international declarations of the WHO, the UN and the World Dental Federation (FDI) were screened. STUDY SELECTION: One the one hand, AI may reduce transportation, optimize care delivery (SDG 3 "Good Health and Well-Being", SDG 13 "Climate Action"), and increase accessibility of services and reduce inequality (SDG 10 "Reduced Inequalities", SDG 4 "Quality Education"). On the other hand, the deployment, implementation and maintenance of AI require significant resources (SDG 12 "Responsible Consumption and Production"), and costs for AI may aggravate inequalities. Also, AI may be biased, reinforcing inequalities (SDG 10) and discrimination (SDG 5), and may violate principles of security, privacy and confidentiality of personal information (SDG 16). CONCLUSIONS: Systematic assessment of the positive impact and adverse effects of AI on sustainable oral health may help to foster the former and curb the latter based on evidence. CLINICAL SIGNIFICANCE: If sustainability imperatives are actively taken into consideration, the community of oral health professionals should then employ AI for improving effectiveness, efficiency, and safety of oral healthcare; strengthen oral health surveillance; foster education and accessibility of care; ensure fairness, transparency and governance of AI for oral health; develop legislation and infrastructure to expand the use of digital health technologies including AI.

Quality of Endodontic Treatment and Prevalence of Apical Radiolucencies in a Bulgarian Subpopulation: a CBCT Analysis.

INTRODUCTION: The advent of Cone Beam Computed Tomography (CBCT) in endodontics has enhanced the diagnosis of periapical radiolucencies and the assessment of endodontically treated teeth. AIM: The purpose of this study was to assess the prevalence of periapical radiolucencies in a Bulgarian subpopulation and the quality of previous endodontic treatment using CBCT scans. MATERIALS AND METHODS: This study included 2795 roots from 160 Large FOV CBCT which were evaluated by two independent examiners using two scoring systems: CBCT-PAI and PESS. RESULTS: The inter-examiner agreement spanned from strong to almost perfect (0.892 and 0.983). The prevalence of periapical lesions according to the two scoring systems was 23.1% and 12.9 %, respectively. The prevalence of endodontically treated teeth was high (34.1%). Sixty-five percent of them presented with signs of periapical radiolucencies, while only 1.4% of all non-treated roots had a periapical lesion. A significant association between periapical disease, poor quality of the root canal filling and inadequate coronal seal was found (p<0.001). CONCLUSIONS: The prevalence of periapical disease in endodontically-treated teeth in the Bulgarian subpopulation was high. Poor qual-ity of the root canal filling and inadequate coronal seal were assessed as prognostic determinants of treatment failure. CBCT techniques can augment conventional diagnostic techniques in the field of endodontics.

The Role of the Immune Response in Chronic Marginal and Apical Periodontitis.

The immune response is a complex, dynamic and strongly individual biologic network that plays an essential role in the pathogenesis of chronic apical and marginal periodontitis. Recent research in the field of periodontology has indicated that the major determinant of susceptibility to disease is the nature of the immunoinflammatory response as marginal periodontal tissue damage is thought to be primarily mediated by the host reaction. Whether the same rules apply for the development of apical periodontitis, however, remains largely unexplored. This review aims to draw parallels between the pathogenesis of chronic periodontitis of endodontic and marginal origin, outline the evidence for the destructive role of immune response in chronic marginal periodontitis and raise questions about its role in chronic apical periodontitis. It would be worthy to further explore the impact of the immune system on the characteristics and progress of these diseases and transfer some of the scientific models from the field of periodontology to the field of endodontics. Research in this area could lead to a more comprehensive understanding of the dynamics of apical and marginal periodontitis and lay the foundation of new personalized treatment strategies.

Biomarker for Asymptomatic Apical Periodontitis in Gingival Crevicular Fluid: aMMP-8.

OBJECTIVES: Asymptomatic apical periodontitis (AAP) is one of the most widespread chronic inflammatory diseases in the field of dental medicine. Active matrix metalloproteinase (aMMP-8) previously demonstrated diagnostic potential as a biomarker for AAP in gingival crevicular fluid (GCF). The aim of this study was to determine the levels and diagnostic accuracy of aMMP-8 in GCF from teeth with AAP. MATERIALS AND METHODS: In this cross-sectional study, GCF samples were obtained from teeth with AAP (sample group, n = 31) and their contralateral teeth (control group, n = 31). Clinical and cone beam computed tomography (CBCT) parameters were used for the diagnosis and assessment of AAP and the determination of clinically healthy marginal periodontal tissues. One pool GCF sample per tooth was obtained from the whole crevice's perimeter. aMMP-8 levels were determined by enzyme-linked immunosorbent assay (ELISA). STATISTICAL ANALYSIS: Wilcoxon signed ranks test and Spearman rank correlation coefficient (rs) were used as statistical tools. The significance level was set at p < .05. RESULTS: The two groups demonstrated biomarker levels corresponding to a healthy marginal periodontal tissue. aMMP-8 levels were statistically and significantly higher in the samples collected from teeth with AAP. Lesions with greater volume showed correspondingly larger diameters. No statistically significant correlation between aMMP-8 levels and lesions' volume or diameter was discovered. CONCLUSION: GCF composition is modified by AAP only to a minimal extent. Further research is needed to substantiate the utilization of aMMP-8 as a potential biomarker for the diagnosis of the disease as well as to explore its relationship with other biomarkers.