Educational aspects of artificial intelligence in oral and maxillofacial radiology: insights from a scoping review

Comprehensive Summary

The study conducted by Satmi et al. compiles evidence of educational integration of artificial intelligence in oral and maxillofacial radiology. This work revealed an increasing interest in learning and training supported by various artificial intelligence models. This study specifically emphasizes the benefits that come from utilizing artificial intelligence during image interpretation, which leads to a more efficient treatment timeline based on increased decision support. Satmi et al. find promising short-term learning gains when using artificial intelligence; however, further research needs to be conducted in order to prove that artificial intelligence can provide long-term competency, allowing it to be integrated into radiology education.

Outcomes and Implications

Findings from this study show the importance of a systematic approach that relates to past methods integrated with artificial intelligence into the field of oral and maxillofacial radiology education. As artificial intelligence becomes more prominent in the workplace, it is crucial that educational programs provide students with adequate resources that lead to technical proficiency and critical understanding. During the integration period, faculty training, collaboration, and evaluation of artificial intelligence methods are required in order to provide efficient use of artificial intelligence in educational outcomes.