Deep Learning-Based Analysis of Dental Imaging Data for Improved Diagnostic Accuracy

Abstract

This research paper explores the application of deep learning techniques to improve the diagnostic accuracy of dental imaging analysis. Dental imaging plays a crucial role in diagnosing various oral health conditions, such as caries, periodontal diseases, and dental anomalies. Traditional diagnostic methods often rely on manual interpretation by dental professionals, which can be subjective and time-consuming. Deep learning models have shown promising results in medical image analysis, including dental imaging, by automating the diagnostic process and enhancing accuracy. This study reviews the current state-of-the-art deep learning approaches for dental imaging analysis and discusses their advantages and limitations. Furthermore, it presents a novel deep learning framework tailored for dental imaging data and evaluates its performance in improving diagnostic accuracy compared to conventional methods. The findings of this research demonstrate the potential of deep learning in revolutionizing dental diagnostic practices, leading to more efficient and accurate patient care.