The use of artificial intelligence to aid in oral hygiene education: A scoping review

Abstract

Objectives: Artificial intelligence (AI) has the potential to aid in constant, non-invasive monitoring of daily oral hygiene practices, potentially on behalf of a dentist or healthcare provider. This review summarises the evidence around the use of AI in the context of oral hygiene education.

Data & sources: This scoping review was developed according to the Joanna Briggs Institute scoping review protocol guidelines and the PRISMA-ScR guidelines. Publications that involved the use of AI for oral hygiene education in any population and setting were included. A systematic electronic database search (MEDLINE via PubMed, EMBASE, Web of Science, Scopus, Cochrane Library, and IEEE Xplore, arXiv, Proquest, Google Scholar, ClinicalTrials.gov, and PROSPERO) up to, and including 4 February 2023 was carried out. Citation searching from the full-text of included publications was also performed.

Results: Of the 3215 publications screened, 20 were selected for qualitative synthesis. These were broadly divided into two categories of AI-assisted feedback: (1) synchronous and (2) asynchronous monitoring. There is a lack of high-quality studies, scarce reflection on possible ethical concerns on AI, and of studies comparing qualitative feedback to quantitative clinical outcomes with a control. Barriers to adoption of AI technologies, patient privacy, and specific areas for improvement were identified.

Conclusion: Within the limitations of this study, the use of AI to modify oral hygiene behaviour is promising. Further work is required in generating higher quality intra-oral images for dental biofilm detection, and in developing more personalised feedback for users.

Clinical significance: This is the first review to map out the available literature on AI in providing oral hygiene education. It may be useful to dental researchers in appraising AI-assisted technologies in the context of oral health.

Keywords: Artificial intelligence; Dental plaque; Machine learning; Oral hygiene; Review.