The introduction of artificial intelligence (AI)-based dental applications into clinical practice could play a significant role in improving diagnostic accuracy and reforming dental care, but its implementation relies on the readiness of dentists, as well as the health system, to adopt it in everyday practice. A cross-sectional anonymous online survey was conducted among experienced dentists and final-year undergraduate students from the School of Dental Medicine at the University of Belgrade (n = 281) in order to investigate their current perspectives and readiness to accept AI into practice. Responders (n = 193) in the present survey, especially final-year undergraduates (n = 76), showed a lack of knowledge about AI (only 7.9% of them were familiar with AI use) and were skeptical (only 34% of them believed that AI should be used), and the underlying reasons, as shown by logistic regression analyses, were a lack of knowledge about the AI technology associated with a fear of being replaced by AI, as well as a lack of regulatory policy. Female dentists perceived ethical issues more significantly than men regarding AI implementation in the practice. The present results encourage an ethical debate on education/training and regulatory policies for AI as a prerequisite for regular AI use in dental practice.

Background: Type 2 diabetes and periodontitis predispose to a higher risk of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection. Recent studies show upregulation of innate immuno‐regulatory microRNA‐146a and ‐155 in oral fluids of patients with type 2 diabetes as well as of patients with periodontitis. The aim was to investigate whether upregulation of these microRNAs may relate to patient susceptibility to the infection via modulation of SARS‐CoV‐2 cellular entry factors expression.Methods: Due to limited experimental feasibility and health risks in Coronavirus Disease 2019, bioinformatic analyses combining with system biology were used as initial investigation of interaction between microRNA‐146 and ‐155 and genes encoding SARS‐CoV‐2 entry factors.Results: SARS‐CoV‐2 cellular entry factors are expressed in salivary glands and masticatory mucosa (tongue) at different expression levels, comparable with those measured in lungs and tonsil. MicroRNA‐146 and ‐155 are widely involved in the regulation of SARS‐CoV‐2 oral cellular entry factors and may enhance expression of ACE2 and modulate genes involved in host immunity.Conclusions: Diabetes‐ and periodontitis‐induced increase in microRNA‐146a and ‐155 in oral cavity is predicted to upregulate angiotensin‐converting enzyme 2 expression, essential SARS‐CoV‐2 entry receptors, and modulate host antiviral response. As it could suggest increased infectivity of diabetes and periodontitis patients, additional protective measures for periodontists are recommended.

The number of approvals for AI-based systems is increasing rapidly, although AI clinical trial designs lack consideration of the impact of human-AI interaction. Aim of this work was to investigate how reading of an AI system (ChatGPT) features/descriptions could influence the willingness and expectations for use of this technology as well as dental students' learning performance. Dental students (N = 104) were asked to learn about side effects of drugs used in dental practice via reading recommended literature or ChatGPT. Expectations towards ChatGPT were measured by survey, before and after reading of a system features description, whilst learning outcomes were evaluated via pharmacology quiz. Students who used ChatGPT (YG group) showed better results on the pharmacology quiz than students who neither read the description nor employed ChatGPT for learning (NN condition). Moreover, students who read the description of ChatGPT features yet did not use it (NG) showed better results on the pharmacology quiz compared with the NN condition, although none of them employed ChatGPT for learning. The NG students compared to the YG students had less trust in AI system assistance in learning, and after the AI system description reading, their expectations changed significantly, showing an association with quiz scores. A majority of students in our cohort was reluctant to use ChatGPT. Furthermore, familarity (reading) with ChatGPT features appear to alter the expectations and enhance learning performance of students.suggesting an AI description-related cognitive bias. Hence the content description of ChatGPTshould be reviewed and verified prior to AI system use for educational purposes.