Exploring the potential of artificial intelligence in paediatric dentistry: A systematic review on deep learning algorithms for dental anomaly detection.

Journal: International journal of paediatric dentistry
PMID: 38297447

Abstract

BACKGROUND: Artificial intelligence (AI) based on deep learning (DL) algorithms has shown promise in enhancing the speed and accuracy of dental anomaly detection in paediatric dentistry.

Authors

  • Henri Hartman
    Doctoral Program, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia.
  • Denny Nurdin
    Department of Conservative Dentistry, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia.
  • Saiful Akbar
    School of Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia.
  • Arief Cahyanto
    Department of Restorative Dentistry, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia.
  • Arlette Suzy Setiawan
    Department of Pediatric Dentistry, Faculty of Dentistry, Universitas Padjadjaran, Bandung, Indonesia.

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