Artificial intelligence in the detection and classification of dental caries.

Journal: The Journal of prosthetic dentistry
Published Date: Aug 26, 2023

Abstract

STATEMENT OF PROBLEM: Automated detection of dental caries could enhance early detection, save clinician time, and enrich treatment decisions. However, a reliable system is lacking.

Authors

  • Walaa Magdy Ahmed
    Assistant Professor, Department of Restorative Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Electronic address: wmahmed@kau.edu.sa.
  • Amr Ahmed Azhari
    Department of Restorative Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia.
  • Khaled Ahmed Fawaz
    Associate Professor, Department of Orthopedic Surgery, Faculty of Medicine, Cairo University, Cairo, Egypt.
  • Hani M Ahmed
    Assistant Professor, Department of Civil Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia.
  • Zainab M Alsadah
    Consultant in Restorative Dentistry, Dental Department, East Jeddah General Hospital, Ministry of Health, Jeddah, Saudi Arabia.
  • Aritra Majumdar
    Graduate student, Department of Computer Science, Computer Science and Applications, Virginia Polytechnic Institute and State University, Blacksburg, Va.
  • Ricardo Marins Carvalho
    Professor, Department of Oral Biological and Medical Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, British Columbia, Canada.

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