Advancing Dental Diagnostics: A Review of Artificial Intelligence Applications and Challenges in Dentistry
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Published:2024-06-07
Issue:6
Volume:8
Page:66
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ISSN:2504-2289
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Container-title:Big Data and Cognitive Computing
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language:en
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Short-container-title:BDCC
Author:
Musleh Dhiaa1, Almossaeed Haya1, Balhareth Fay1, Alqahtani Ghadah1, Alobaidan Norah1, Altalag Jana1, Aldossary May Issa2
Affiliation:
1. Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia 2. Department of Computer Information Systems, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
Abstract
The rise of artificial intelligence has created and facilitated numerous everyday tasks in a variety of industries, including dentistry. Dentists have utilized X-rays for diagnosing patients’ ailments for many years. However, the procedure is typically performed manually, which can be challenging and time-consuming for non-specialized specialists and carries a significant risk of error. As a result, researchers have turned to machine and deep learning modeling approaches to precisely identify dental disorders using X-ray pictures. This review is motivated by the need to address these challenges and to explore the potential of AI to enhance diagnostic accuracy, efficiency, and reliability in dental practice. Although artificial intelligence is frequently employed in dentistry, the approaches’ outcomes are still influenced by aspects such as dataset availability and quantity, chapter balance, and data interpretation capability. Consequently, it is critical to work with the research community to address these issues in order to identify the most effective approaches for use in ongoing investigations. This article, which is based on a literature review, provides a concise summary of the diagnosis process using X-ray imaging systems, offers a thorough understanding of the difficulties that dental researchers face, and presents an amalgamative evaluation of the performances and methodologies assessed using publicly available benchmarks.
Reference43 articles.
1. Application of Artificial Intelligence in Dentistry;Shan;J. Dent. Res.,2021 2. Martins, M.V., Baptista, L., Luís, H., Assunção, V., Araújo, M.-R., and Realinho, V. (2023). Machine Learning in X-ray Diagnosis for Oral Health: A Review of Recent Progress. Computation, 11. 3. How Does Artificial Intelligence Impact Digital Healthcare Initiatives? A Review of AI Applications in Dental Healthcare;Mahdi;Int. J. Inf. Manag. Data Insights,2023 4. Shafi, I., Fatima, A., Afzal, H., Díez, I.d.l.T., Lipari, V., Breñosa, J., and Ashraf, I. (2023). A Comprehensive Review of Recent Advances in Artificial Intelligence for Dentistry E-Health. Diagnostics, 13. 5. Transforming Dental Caries Diagnosis Through Artificial Intelligence-Based Techniques;Anil;Cureus,2023
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