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REVIEW article

Front. Dent. Med
Sec. Reconstructive Dentistry
Volume 5 - 2024 | doi: 10.3389/fdmed.2024.1525505
This article is part of the Research Topic Revolutionizing Dentistry: The Impact of AI and new Algorithms on Diagnostics, Treatment, and Patient Engagement View all articles

Artificial Intelligence Dentistry and Dental Biomaterials

Provisionally accepted
Dinesh Rokaya Dinesh Rokaya 1Ahmad Al Jaghsi Ahmad Al Jaghsi 1,2Rohan Jagtap Rohan Jagtap 3Viritpon Srimaneepong Viritpon Srimaneepong 4*
  • 1 College of Dentistry, Ajman University, Ajman, United Arab Emirates
  • 2 Universitätsmedizin Greifswald, Greifswald, Mecklenburg-Vorpommern, Germany
  • 3 University of Mississippi Medical Center School of Dentistry, Jackson, Mississippi, United States
  • 4 Chulalongkorn University, Bangkok, Bangkok, Thailand

The final, formatted version of the article will be published soon.

    Artificial intelligence (AI) technology is being used in various fields and its use is increasingly expanding in dentistry. The key aspects of AI include machine learning (ML), deep learning (DL), and neural networks (NNs). The aim of this review is to present an overview of AI, its various aspects, and its application in biomedicine, dentistry, and dental biomaterials focusing on restorative dentistry and prosthodontics. AI-based systems can be a complementary tool in diagnosis and treatment planning, result prediction, and patient-centered care. AI software can be used to detect restorations, prosthetic crowns, periodontal bone loss, and root canal segmentation from the periapical radiographs. The integration of AI, digital imaging, and 3D printing can provide more precise, durable, and patient-oriented outcomes. AI can be also used for the automatic segmentation of panoramic radiographs showing normal anatomy of the oral and maxillofacial area. Recent advancement in AI in medical and dental sciences includes multimodal deep learning fusion, speech data detection, and neuromorphic computing. Hence, AI has helped dentists in diagnosis, planning, and aid in providing high-quality dental treatments in less time.

    Keywords: artificial intelligence, machine learning, deep learning, neural networks, Medicine, Dentistry, Dental medicine, Dental biomaterials

    Received: 09 Nov 2024; Accepted: 06 Dec 2024.

    Copyright: © 2024 Rokaya, Al Jaghsi, Jagtap and Srimaneepong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Viritpon Srimaneepong, Chulalongkorn University, Bangkok, 10330, Bangkok, Thailand

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.