Full paper: Büttner, M., Rokhshad, R., Brinz, J., Issa, J., Chaurasia, A., Uribe, S.E., Karteva, T., Chala, S., Tichy, A., Schwendicke, F., 2024. Core outcomes measures in dental computer vision studies (DentalCOMS). J. Dent. 150, 105318. https://doi.org/10.1016/j.jdent.2024.105318

This scoping review examines existing university and organisational guidelines on integrating generative AI (GenAI), such as ChatGPT, into education, focusing on recommendations for academic staff. The authors analysed 31 documents from various institutions and organisations globally, identifying common themes like ethical use, transparency, and academic integrity. A significant lack of dental-specific guidance was highlighted, prompting recommendations for creating comprehensive guidelines that address ethical concerns, prevent misuse, and promote critical thinking. The review also discusses the need for AI literacy training and infrastructure investment to facilitate effective GenAI integration in dental education. Finally, the authors suggest that dental institutions should adapt with the same urgency shown during the COVID-19 pandemic to successfully integrate this technology.

Paper: Uribe, S.E., Maldupa, I., Schwendicke, F., 2025. Integrating Generative AI in Dental Education: A Scoping Review of Current Practices and Recommendations. Eur. J. Dent. Educ. https://doi.org/10.1111/eje.13074

In this episode, we explore the state of transparency in dental research, based on a large-scale analysis of the dental literature. The study examined over 10,000 articles from PubMed-indexed dental journals, assessing key transparency practices such as data sharing, code sharing, and conflict of interest disclosure. While some practices, like funding disclosures, are improving, data and code sharing remain rare. Join us as we discuss what these findings mean for the future of research integrity and why dental science needs more openness to drive progress.

Full text: Research transparency in dental research: A programmatic analysis

In this episode, we explore the global prevalence of early childhood caries (ECC), a condition affecting nearly half of preschool-aged children around the world. This systematic review and meta-analysis done by Sergio Uribe, Ilze Maldupa, and Nicola Innes examines data from 29 countries and the last 20 years, using the World Health Organization's diagnostic criteria. We discuss the significant variations in ECC prevalence between countries and what these findings mean for global efforts to improve children's oral health.

Full text: The global prevalence of early childhood caries: A systematic review with meta-analysis using the WHO diagnostic criteria

In this episode, we explore the evolution of cariology, covering key concepts in the epidemiology, diagnosis, etiology, and treatment of dental caries. Co-authors Santiago Gómez and Sergio Uribe provide a concise review for dental professionals, discussing how caries pathology is driven by biofilm dysbiosis, the importance of risk-based diagnostics, and the shift towards minimally invasive treatments. Looking ahead, we delve into how advances in sugar reduction strategies, microbiome research, artificial intelligence, and biomimetic materials could pave the way for personalized oral health care. Tune in to discover how scientific progress can shape the future of dental practice!

Full text (in spanish): Past, Present, and Future of Cariology.

In this episode, we tackle the pressing issue of data sharing in dental research. Using the FAIR principles—Findable, Accessible, Interoperable, and Reusable—we explore why open data is crucial for advancing dental science and improving patient care. Despite the potential for machine learning to revolutionize dentistry, our analysis shows that only 1.5% of dental research data is shared, and much of it falls short of FAIR standards. Tune in to find out what’s missing in dental research and why sharing data is the key to future innovation!

Full paper: Dental Research Data Availability and Quality According to the FAIR Principles

In this episode, we explore the intriguing but still evolving role of artificial intelligence in caries detection. We discuss a systematic review of deep learning models, highlighting impressive accuracy rates reported by various studies. However, much of the evidence comes from poorly designed or inadequately reported research, and there are no clinical trials to confirm these findings. Could AI one day assist dentists in detecting caries more reliably? While the results are promising, we’ll take a closer look at the research gaps and what this means for the future of dental care.

Full paper: Deep learning for caries detection: A systematic review

In this episode, we examine the national impact of the COVID-19 pandemic on dental services, based on a study led by Ilze Maldupa, Sergio Uribe, and their colleagues. Discover how public health restrictions during the pandemic caused an 81.6% drop in routine dental care, how services rebounded, and what this means for future health care resilience. We explore the broader implications for national dental care systems and the lessons learned in adapting to unprecedented challenges.

Full text: Effect of COVID-19 on Coverage of Dental Services in Latvia