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Review
. 2023 Feb 20:4:1085251.
doi: 10.3389/fdmed.2023.1085251. eCollection 2023.

Artificial intelligence in dentistry-A review

Hao Ding  1 , Jiamin Wu  1 , Wuyuan Zhao  1 , Jukka P Matinlinna  1   2 , Michael F Burrow  3 , James K H Tsoi  1
Affiliations
Review

Artificial intelligence in dentistry-A review

Hao Ding et al. Front Dent Med. .

Abstract

Artificial Intelligence (AI) is the ability of machines to perform tasks that normally require human intelligence. AI is not a new term, the concept of AI can be dated back to 1950. However, it did not become a practical tool until two decades ago. Owing to the rapid development of three cornerstones of current AI technology-big data (coming through digital devices), computational power, and AI algorithm-in the past two decades, AI applications have started to provide convenience to people's lives. In dentistry, AI has been adopted in all dental disciplines, i.e., operative dentistry, periodontics, orthodontics, oral and maxillofacial surgery, and prosthodontics. The majority of the AI applications in dentistry are for diagnosis based on radiographic or optical images, while other tasks are not as applicable as image-based tasks mainly due to the constraints of data availability, data uniformity, and computational power for handling 3D data. Evidence-based dentistry (EBD) is regarded as the gold standard for decision making by dental professionals, while AI machine learning (ML) models learn from human expertise. ML can be seen as another valuable tool to assist dental professionals in multiple stages of clinical cases. This review describes the history and classification of AI, summarizes AI applications in dentistry, discusses the relationship between EBD and ML, and aims to help dental professionals better understand AI as a tool to support their routine work with improved efficiency.

Keywords: artficial intelligence (AI); dentistry; evidence-based dentistry; machine learning; neural network.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Schematic diagram of the relationship between AI, strong AI, weak AI, expert-based systems, machine learning, deep learning and neural network (NN).
Figure 2
Figure 2
Schematic diagram of deep learning.
See this image and copyright information in PMC

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