Artificial Intelligence in Dental Imaging Practice among Oral Radiologists from the City of Chennai: A Qualitative...

Artificial intelligence (AI) has the potential to significantly transform the role of the doctor and revolutionize the practice of medicine and radiology. Studies have documented the clinical potentials of AI in medical imaging practice to improving patient care. There are no studies done in India that assess the attitude and perspectives of oral radiologists toward AI in dental radiology.

The present study aimed to identify barriers and enablers for the implementation of AI in dental radiology.

The study employs a qualitative design using an open-ended instrument. The sample size was 35 oral radiologists who were working within the district of Chennai and convenience/snowball sampling was done. Data obtained were analyzed using qualitative content analysis. Six themes of concerns were generated: expectant tool; career insecurity; cost of new technology; equipment preservation and data insecurity; service delivery quality; need for expanding AI awareness. A questionnaire developed along the Theoretical Domains Framework and the Capabilities, Opportunities, and Motivations influencing Behaviors model was used to guide interviews. Mayring's content analysis was employed to point out barriers and enablers.

In the current study, nine themes were identified as enablers, four as conflicting themes, and seven as barriers for the acceptance of AI-integrated radiology. The factors that influence the radiology field and their attitude toward the introduction of AI in dental radiology were assessed thoroughly. Both stakeholders emphasized chances and hopes for AI along with marginal fear of job insecurity. A range of enablers for implementing AI in dental diagnostics was identified (e.g., the chance for higher diagnostic accuracy, a reduced workload, more comprehensive reporting, and better patient-provider communication).

AI has an important role to play in the global health care setting. The current study reported the attitudes and apprehensions of oral radiologists toward AI integration in radiology. Decision-makers and radiology industry may want to consider the barriers and conflicting themes that appear as challenges to foster implementation of AI in dentistry.