AI-assisted versus traditional radiographic interpretation for early caries detection.

Early detection of dental caries is critical for implementing effective preventive measures, yet traditional radiographic interpretation often lacks consistency due to observer variability. Therefore, it is of interest to compare the diagnostic performance of AI-assisted and conventional radiographic interpretations for detecting early carious lesions. Hence, a total of 100 subjects were randomly assigned to either the AI-assisted or conventional interpretation group, with diagnostic accuracy assessed using sensitivity, specificity and overall accuracy. Thus, we show that AI-assisted interpretation outperformed conventional methods, with higher sensitivity (84%) and diagnostic accuracy (82%). This advancement highlights AI's potential to significantly improve early caries detection in dental practice.