With the development of the European Academy of Paediatric Dentistry (EAPD) judgment criteria, there has been increasing interest worldwide in investigation of the prevalence of demarcated opacities in tooth enamel substance, known as molar–incisor hypomineralisation (MIH). However, the lack of a standardised system for the purpose of recording MIH data in epidemiological surveys has contributed greatly to the wide variations in the reported prevalence between studies. The present publication describes the rationale, development, and content of a scoring method for MIH diagnosis in epidemiological studies as well as clinic- and hospital-based studies. The proposed grading method allows separate classification of demarcated hypomineralisation lesions and other enamel defects identical to MIH. It yields an informative description of the severity of MIH-affected teeth in terms of the stage of visible enamel destruction and the area of tooth surface affected (i.e. lesion clinical status and extent, respectively). In order to preserve the maximum amount of information from a clinical examination consistent with the need to permit direct comparisons between prevalence studies, two forms of the charting are proposed, a short form for simple screening surveys and a long form desirable for prospective, longitudinal observational research where aetiological factors in demarcated lesions are to be investigated in tandem with lesions distribution. Validation of the grading method is required, and its reliability and usefulness need to be tested in different age groups and different populations.

We conducted a systematic review of teledentistry applications. We searched the MEDLINE/PubMed, Embase and Cochrane Library databases for relevant articles published from 1992 to 2012. The reference lists of all retrieved articles were hand-searched. Studies were included after assessing the eligibility of the full-text article. A total of 878 studies were identified, of which 59 fulfilled the inclusion criteria of the review. The articles covered several dental specialties, mostly oral surgery, oral medicine and oral pathology. The most common type of teledentistry application was education ( n = 21), followed by diagnosis ( n = 1 6), consultation ( n = 3) and treatment ( n = 2). Teledentistry studies were reported in a total of 15 countries. The largest number of studies were conducted in the US ( n = 22) and there were no studies from developing countries. Most of the reports referred to pilot projects and short-term outcomes, and most of the studies were descriptive. The review indicates that although teledentistry is an area of expansion, there are still some barriers to its increased use.

Introduction: Interest is growing in the potential of artificial intelligence (AI) chatbots and large language models like OpenAI's ChatGPT and Google's Gemini, particularly in dental education. To explore dental educators‘ perceptions of AI chatbots and large language models, specifically their potential benefits and challenges for dental education.Materials and Methods: A global cross‐sectional survey was conducted in May–June 2023 using a 31‐item online‐questionnaire to assess dental educators' perceptions of AI chatbots like ChatGPT and their influence on dental education. Dental educators, representing diverse backgrounds, were asked about their use of AI, its perceived impact, barriers to using chatbots, and the future role of AI in this field.Results: 428 dental educators (survey views = 1516; response rate = 28%) with a median [25/75th percentiles] age of 45 [37, 56] and 16 [8, 25] years of experience participated, with the majority from the Americas (54%), followed by Europe (26%) and Asia (10%). Thirty‐one percent of respondents already use AI tools, with 64% recognising their potential in dental education. Perception of AI's potential impact on dental education varied by region, with Africa (4[4–5]), Asia (4[4–5]), and the Americas (4[3–5]) perceiving more potential than Europe (3[3–4]). Educators stated that AI chatbots could enhance knowledge acquisition (74.3%), research (68.5%), and clinical decision‐making (63.6%) but expressed concern about AI's potential to reduce human interaction (53.9%). Dental educators' chief concerns centred around the absence of clear guidelines and training for using AI chatbots.Conclusion: A positive yet cautious view towards AI chatbot integration in dental curricula is prevalent, underscoring the need for clear implementation guidelines.