Knowledge Attitude and Practices of Dental Students and Dental Practitioners Towards Artificial Intelligence
Keywords:Attitude, Clinical Decision Support System, Deep Learning, Dental Education, Surveys, questionnaires
Background: Artificial intelligence (A.I.) and its subsets, machine learning (ML) and deep learning (DL), have been developed to analyze complex data obtained from various sources using algorithms integrated into decision support systems (D.S.S.s).DL algorithms in dentistry are useful in various diagnostic and treatment modalities. However, very few literature follow-up surveys and multi-regional studies were conducted to explore the practice of A.I. by dental professionals
Aim: The present study aimed to evaluate the knowledge, attitude, and practices of dental students as well as dental practitioners toward artificial intelligence
Methodology: A 15-question survey was prepared and distributed through Google Forms among dental students and professionals across Tamil Nadu, India. It comprised various sections aiming to evaluate the knowledge, attitude, and practice toward A.I. and its potential applications in dentistry.
Results: 200 dental students and professionals (101 female, 99 male) responded to the questionnaire. Of these, about 70% (interns), 78.97% (Post graduates), and 77.95% (Dentists with less than five years of experience) had basic knowledge about A.I. technologies. Only 39.5% (p<.05)agreed A.I. has potential application both in the field of medicine and dentistry, but 53.5% (p<.05)thinks A.I. cannot replace the role of the dentist either in patient management or diagnosis shortly. In addition, 53.5% are aware of the potential applications; 44% recommended A.I. to be included in the undergraduate and postgraduate dental curriculum.
Conclusion: The present study results indicate that most dental students and practitioners with less than 5year of experience are aware of A.I. but lack basic knowledge about incorporation and working models. Most participants emphasized that the basic working principles of A.I., such as data science and logical statistics, should be taught in dentistry as a part of the curriculum or as value-added courses during their clinical training. Thus demanding the need for better evidence-based teaching with the expanded application of A.I. tools in dental practice.
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