Artificial intelligence-assisted full-mouth radiograph mounting in dental education.

Journal: Journal of dental education
PMID: 38545660

Abstract

OBJECTIVES: With the increasing prevalence of artificial intelligence (AI) and the significant research gap in the application of AI within dentistry, this study aimed to (1) evaluate the efficiency and accuracy of dental students in full-mouth radiograph series (FMS) mounting with and without AI assistance, and (2) assess dental students' perceptions of AI in clinical education to address the impact of AI in dental education.

Authors

  • Jennifer Chang
    Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA. Jennifer.chang@uth.tmc.edu.
  • Logan Bliss
    School of Dentistry, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
  • Nikola Angelov
    Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
  • Aaron Glick
    Department of General Practice and Dental Public Health, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.

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