Journal of AdvancedMedical and Dental Sciences Research

Background: The integration of artificial intelligence (AI) in healthcare has shown significant promise in improving diagnostic accuracy and efficiency. Dentistry, being an essential part of healthcare, can benefit from AI applications for disease detection. Aim and Objectives: Objective: The study aimed to assess and compare the efficiency of an artificial intelligence (AI) model and experienced dentists in detecting dental diseases through the analysis of clinical photographs. Methodology: A diverse collection of clinical images depicting various dental conditions was compiled to form a comprehensive dataset. A deep learning AI model named DentalFriend was trained on this dataset to recognize and classify different dental diseases. The AI model's performance was subsequently evaluated against diagnoses provided by skilled and experienced dentists. The evaluation encompassed several key factors: diagnostic accuracy, processing speed, error rate, cost-effectiveness, and ethical considerations. Results: The results of the evaluation revealed promising outcomes regarding the integration of AI in dental disease detection. The AI model demonstrated a commendable level of diagnostic accuracy, comparable to that of experienced dentists. The processing speed of the AI model significantly outperformed human dentists, leading to quicker analyses and potentially expedited treatment decisions. The error rate exhibited by the AI model was comparable to or lower than that of human counterparts, showcasing its reliability in clinical applications. Cost-effectiveness emerged as a noteworthy advantage of AI integration. The initial investment in training and implementing the AI system was counterbalanced by its potential to provide consistent, accurate, and swift diagnoses, reducing the need for multiple consultations and repetitive examinations. Conclusions: The study underscores the potential of AI as a valuable tool in dental disease detection. The AI model exhibited competitive diagnostic accuracy, superior processing speed, and promising cost-effectiveness. However, it also emphasized the irreplaceable role of experienced dentists in intricate cases, highlighting the significance of collaborative AI-human synergy in optimizing patient care. This research advocates for a balanced integration of AI technologies within the dental field, driven by a commitment to enhancing diagnostic efficiency and overall healthcare outcomes.