Comparing the effectiveness of two diagnostic approaches for the interpretation of oral radiographic lesions by dental students.

Interpreting radiographic lesions on dental radiographs is a challenging process especially for novice learners, and there is a lack of tools available to support this diagnostic process. This study introduced dental students to two diagnostic aids with contrasting reasoning approaches-ORAD DDx, which uses an analytic, forward reasoning approach, and a Radiographic Atlas, which emphasizes a non-analytic, backward reasoning approach. We compared the effectiveness of ORAD DDx and the Atlas in improving students' diagnostic accuracy and their ability to recall features of radiographic lesions. Participants (99 third-year dental students) were assigned to ORAD DDx, Atlas and Control groups. In the pre-test and post-test, participants provided their diagnosis for eight types of radiographic lesions. All groups also completed a Cued Recall Test. Feedback about ORAD DDx and the Atlas was collected. Results indicated that the Atlas was more effective than ORAD DDx in improving diagnostic accuracy (Estimated marginal mean difference = 1.88 (95% CI 0.30-3.46), p = 0.014, Cohen's d = 0.714). Participants in the Atlas group also outperformed the Control group in the recall of the lesions' radiographic features (Estimated marginal mean difference = 3.42 (95% CI 0.85-5.99), p = 0.005, Cohen's d = 0.793). Students reported that both ORAD DDx and Atlas increased their confidence and decreased the mental effort required to develop differential diagnosis (p ≤ 0.001). This study demonstrates the effectiveness of a non-analytic approach in interpreting dental radiographs among novice learners through the novel use of diagnostic aids.

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

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.