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

In this episode, we dive into the latest research on fluoride use in toothpastes across Latvia and Lithuania. Join us as we discuss the surprising findings from a survey of over 5,000 individuals, revealing gaps in fluoride toothpaste usage—especially among children. Co-authors Ilze Maldupa, Julija Narbutaite, and Sergio Uribe explore the implications of these choices for public health and the steps needed to ensure effective caries prevention. Should we be concerned about non-fluoride toothpaste? Tune in to find out!

Full paper Should we be concerned about the use of non-fluoride toothpaste? A survey study in two European countries

Artificial intelligence (AI) holds immense potential for revolutionizing dental diagnostics, treatment planning, and research. However, developing and validating robust and reliable AI algorithms hinges on the availability of high-quality, diverse, and ethically sourced dental imaging datasets. This episode cover the Journal of Dental Research publication by Dr Sergio Uribe and the ITU/WHO Global Initiative on AI for Health, about the the current landscape of publicly available dental imaging datasets. It examines the challenges and opportunities presented by these datasets, including issues related to data scarcity, metadata completeness, and adherence to FAIR principles (Findability, Accessibility, Interoperability, and Reusability). This chapter also highlights the need for increased data diversity to mitigate algorithmic bias and ensure the development of generalizable AI tools to diverse populations worldwide. You can read the full text here: Publicly Available Dental Image Datasets for Artificial Intelligence