RT info:eu-repo/semantics/article T1 A comprehensive review of recent advances in artificial intelligence for dentistry E-health A1 Shafi, Imran A1 Fatima, Anum A1 Afzal, Hammad A1 Torre Díez, Isabel de la A1 Lipari, Vivian A1 Breñosa, Jose A1 Ashraf, Imran K1 Medical informatics K1 Medicina - Informática K1 Dentistry K1 Odontología K1 Medical care K1 Machine learning K1 Artificial intelligence K1 Image processing K1 Imágenes, Tratamiento de las K1 Diagnostic imaging K1 Imágenes médicas K1 1203.17 Informática K1 1203.04 Inteligencia Artificial K1 32 Ciencias Médicas K1 3212 Salud Publica AB Artificial intelligence has made substantial progress in medicine. Automated dental imaging interpretation is one of the most prolific areas of research using AI. X-ray and infrared imaging systems have enabled dental clinicians to identify dental diseases since the 1950s. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, and machine- and deep-learning models for dental disease diagnoses using X-ray and near-infrared imagery. Despite the notable development of AI in dentistry, certain factors affect the performance of the proposed approaches, including limited data availability, imbalanced classes, and lack of transparency and interpretability. Hence, it is of utmost importance for the research community to formulate suitable approaches, considering the existing challenges and leveraging findings from the existing studies. Based on an extensive literature review, this survey provides a brief overview of X-ray and near-infrared imaging systems. Additionally, a comprehensive insight into challenges faced by researchers in the dental domain has been brought forth in this survey. The article further offers an amalgamative assessment of both performances and methods evaluated on public benchmarks and concludes with ethical considerations and future research avenues. PB MDPI SN 2075-4418 YR 2023 FD 2023 LK https://uvadoc.uva.es/handle/10324/66484 UL https://uvadoc.uva.es/handle/10324/66484 LA eng NO Diagnostics, 2023, Vol. 13, Nº. 13, 2196 NO Producción Científica DS UVaDOC RD 23-may-2024