Artificial Intelligence Applications in Dentistry
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Invited Paper
P: 52-55
March 2022

Artificial Intelligence Applications in Dentistry

J Ankara Univ Fac Med 2022;75(1):52-55
1. Girne Üniversitesi Diş Hekimliği Fakültesi, Periodontoloji Anabilim Dalı, Girne, Kıbrıs
2. Ankara Üniversitesi Diş Hekimliği Fakültesi, Radyoloji Anabilim Dalı, Ankara, Türkiye
3. Ankara Üniversitesi Medikal Tasarım ve Uygulama Merkezi (MEDITAM), Ankara, Türkiye
4. Lublin Medical University, Department of Dentistry, Lublin, Poland
No information available.
No information available
Received Date: 11.11.2022
Accepted Date: 23.11.2022
Publish Date: 18.01.2023
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ABSTRACT

Artificial intelligence (AI) represents the learning and problem-solving capacity of machines that mimic humans’ cognitive functions. Unlike a single clinician, AI systems can simultaneously observe and rapidly process an unlimited amount of data. Machine learning includes computational models and algorithms called artificial neural networks (ANNs) that mimic the architecture of biological neural networks in the brain. Artificial intelligence applications have become popular in many areas of dentistry as well as in medicine. This review focuses on artificial intelligence applications in various fields of dentistry and related studies with a comprehensive literature review. AI can be used in oral and maxillofacial surgery (determination of anatomical landmarks, prediction of postoperative complications), periodontology (determination of alveolar bone loss and changes in bone density), implantology, oral and maxillofacial radiology (tooth segmentation, identification of extra teeth, root fractures or apical lesions, in the prediction of osteoporosis), restorative dentistry (determination of dental caries), and orthodontics (treatment analysis, skeletal classification and determination of growth and development period). Integrating artificial intelligence technology into dentistry aims to minimize human mistakes while saving cost and time, especially in clinics where the number of clinicians is low.

Keywords: Artificial Intelligence, Deep Learning Model, Dentistry, Applications

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