Objective: The advent of AI in the field of dentistry and in forensic odontology is gaining momentum in the recent times. The current systematic review aims to determine the use of AI in dental age estimation.
Methods: Using PRISMA guidelines, original articles from “PubMed”, “Scopus” and “Google Scholar” were searched using terms, viz “dental age estimation”; “artificial intelligence”; “neural networks”; and “convolution networks” from the period of 2017 to present. Inclusion criteria included English language original research with completely free access. Non-English, in vitro studies, and abstract only articles were excluded from the study.
Results: Total 11 articles were included in the study. The studies were retrospective in nature. The studies showed that AI-based applications estimate the dental age more precisely and in a large population. The majority of the studies used machine learning, deep convolutional networks, and deep learning types of AI in their study.
Conclusion: The use of AI in age estimation is an excellent tool for dental age estimation of large populations with precision. Further, large-scale studies using other imaging modalities are recommended.