The Use of Artificial Intelligence in Caries Detection: A Review

• Published in: Bioengineering (Basel) Vol. 11; no. 9; p. 936
• Main Authors: Al-Khalifa, Khalifa S, Ahmed, Walaa Magdy, Azhari, Amr Ahmed, Qaw, Masoumah, Alsheikh, Rasha, Alqudaihi, Fatema, Alfaraj, Amal
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 18-09-2024; MDPI
• Subjects: Accuracy; Algorithms; Artificial intelligence; Artificial neural networks; Clinical medicine; Computational linguistics; Datasets; Dental caries; Dental materials; Dentistry; Dentists; detection; Development and progression; diagnosis; Diagnostic tests; Disease prevention; Fluorides; Health aspects; Language processing; Lasers; Morphology; Natural language interfaces; Neural networks; Oral hygiene; Review; Risk assessment; Toiletries industry; treatment planning; dental caries; treatment planning; diagnosis; detection; artificial intelligence
• ISSN: 2306-5354; 2306-5354
• DOI: 10.3390/bioengineering11090936

Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This review critically examines the current state of AI applications in caries detection, focusing on the performance and accuracy of various AI techniques. We evaluated 40 studies from the past 23 years, carefully selected for their relevance and quality. Our analysis highlights the potential of AI, especially convolutional neural networks (CNNs), to improve diagnostic accuracy and efficiency in detecting dental caries. The findings underscore the transformative potential of AI in clinical dental practice.