CC BY-NC-ND 4.0 · Eur J Dent 2018; 12(04): 594-601
DOI: 10.4103/ejd.ejd_325_18
Review Article
Dental Investigation Society

History and application of artificial neural networks in dentistry

Wook Joo Park
1   Department of Philosophy of Religion, College of Theology, The United Graduate School of Theology in Yonsei University, Seoul, Republic of Korea
,
Jun-Beom Park
2   Department of Periodontics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
› Author Affiliations
Further Information

Publication History

Publication Date:
23 September 2019 (online)

ABSTRACT

Artificial intelligence (AI) is a commonly used term in daily life, and there are now two subconcepts that divide the entire range of meanings currently encompassed by the term. The coexistence of the concepts of strong and weak AI can be seen as a result of the recognition of the limits of mathematical and engineering concepts that have dominated the definition. This presentation reviewed the concept, history, and the current application of AI in daily life. Applications of AI are becoming a reality that is commonplace in all areas of modern human life. Efforts to develop robots controlled by AI have been continuously carried out to maximize human convenience. AI has also been applied in the medical decision-making process, and these AI systems can help nonspecialists to obtain expert-level information. Artificial neural networks are highly interconnected networks of computer processors inspired by biological nervous systems. These systems may help connect dental professionals all over the world. Currently, the use of AI is rapidly advancing beyond text-based, image-based dental practice. This presentation reviewed the history of artificial neural networks in the medical and dental fields, as well as current application in dentistry. As the use of AI in the entire medical field increases, the role of AI in dentistry will be greatly expanded. Currently, the use of AI is rapidly advancing beyond text-based, image-based dental practice. In addition to diagnosis of visually confirmed dental caries and impacted teeth, studies applying machine learning based on artificial neural networks to dental treatment through analysis of dental magnetic resonance imaging, computed tomography, and cephalometric radiography are actively underway, and some visible results are emerging at a rapid pace for commercialization.

 
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