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Artificial intelligence in endodontics: Fundamental principles, workflow, and tasks.

Authors :
Ourang, Seyed AmirHossein
Sohrabniya, Fatemeh
Mohammad‐Rahimi, Hossein
Dianat, Omid
Aminoshariae, Anita
Nagendrababu, Venkateshbabu
Dummer, Paul Michael Howell
Duncan, Henry F.
Nosrat, Ali
Source :
International Endodontic Journal; Nov2024, Vol. 57 Issue 11, p1546-1565, 20p
Publication Year :
2024

Abstract

The integration of artificial intelligence (AI) in healthcare has seen significant advancements, particularly in areas requiring image interpretation. Endodontics, a specialty within dentistry, stands to benefit immensely from AI applications, especially in interpreting radiographic images. However, there is a knowledge gap among endodontists regarding the fundamentals of machine learning and deep learning, hindering the full utilization of AI in this field. This narrative review aims to: (A) elaborate on the basic principles of machine learning and deep learning and present the basics of neural network architectures; (B) explain the workflow for developing AI solutions, from data collection through clinical integration; (C) discuss specific AI tasks and applications relevant to endodontic diagnosis and treatment. The article shows that AI offers diverse practical applications in endodontics. Computer vision methods help analyse images while natural language processing extracts insights from text. With robust validation, these techniques can enhance diagnosis, treatment planning, education, and patient care. In conclusion, AI holds significant potential to benefit endodontic research, practice, and education. Successful integration requires an evolving partnership between clinicians, computer scientists, and industry. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01432885
Volume :
57
Issue :
11
Database :
Complementary Index
Journal :
International Endodontic Journal
Publication Type :
Academic Journal
Accession number :
181569637
Full Text :
https://doi.org/10.1111/iej.14127