Developing an AI-Powered Algorithm for Automated Detection and Classification of Dental Caries from Intraoral Radiographs: A Machine Learning Approach

This systematic review aims to assess the diagnostic accuracy of artificial intelligence (AI) models specifically developed for detecting and classifying dental caries. A comprehensive electronic literature search was performed on the PubMed, Web of Science, SCOPUS, and Embase databases. The search...

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Main Author: Mohammad Haider
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2024-12-01
Series:Journal of Pharmacy and Bioallied Sciences
Subjects:
Online Access:https://journals.lww.com/10.4103/jpbs.jpbs_1097_24
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author Mohammad Haider
author_facet Mohammad Haider
author_sort Mohammad Haider
collection DOAJ
description This systematic review aims to assess the diagnostic accuracy of artificial intelligence (AI) models specifically developed for detecting and classifying dental caries. A comprehensive electronic literature search was performed on the PubMed, Web of Science, SCOPUS, and Embase databases. The search yielded a total of 397 results. We examined 10 articles that satisfied the selection criteria. In summary, AI-based models show high diagnostic accuracy in recognizing dental caries by analyzing dental radiography pictures.
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institution Kabale University
issn 0976-4879
0975-7406
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publishDate 2024-12-01
publisher Wolters Kluwer Medknow Publications
record_format Article
series Journal of Pharmacy and Bioallied Sciences
spelling doaj-art-f869cddc30764f68ae0271b10d5b5dfc2025-01-12T14:04:23ZengWolters Kluwer Medknow PublicationsJournal of Pharmacy and Bioallied Sciences0976-48790975-74062024-12-0116Suppl 4S3089S309110.4103/jpbs.jpbs_1097_24Developing an AI-Powered Algorithm for Automated Detection and Classification of Dental Caries from Intraoral Radiographs: A Machine Learning ApproachMohammad HaiderThis systematic review aims to assess the diagnostic accuracy of artificial intelligence (AI) models specifically developed for detecting and classifying dental caries. A comprehensive electronic literature search was performed on the PubMed, Web of Science, SCOPUS, and Embase databases. The search yielded a total of 397 results. We examined 10 articles that satisfied the selection criteria. In summary, AI-based models show high diagnostic accuracy in recognizing dental caries by analyzing dental radiography pictures.https://journals.lww.com/10.4103/jpbs.jpbs_1097_24artificial intelligenceclassificationdental cariesdetection
spellingShingle Mohammad Haider
Developing an AI-Powered Algorithm for Automated Detection and Classification of Dental Caries from Intraoral Radiographs: A Machine Learning Approach
Journal of Pharmacy and Bioallied Sciences
artificial intelligence
classification
dental caries
detection
title Developing an AI-Powered Algorithm for Automated Detection and Classification of Dental Caries from Intraoral Radiographs: A Machine Learning Approach
title_full Developing an AI-Powered Algorithm for Automated Detection and Classification of Dental Caries from Intraoral Radiographs: A Machine Learning Approach
title_fullStr Developing an AI-Powered Algorithm for Automated Detection and Classification of Dental Caries from Intraoral Radiographs: A Machine Learning Approach
title_full_unstemmed Developing an AI-Powered Algorithm for Automated Detection and Classification of Dental Caries from Intraoral Radiographs: A Machine Learning Approach
title_short Developing an AI-Powered Algorithm for Automated Detection and Classification of Dental Caries from Intraoral Radiographs: A Machine Learning Approach
title_sort developing an ai powered algorithm for automated detection and classification of dental caries from intraoral radiographs a machine learning approach
topic artificial intelligence
classification
dental caries
detection
url https://journals.lww.com/10.4103/jpbs.jpbs_1097_24
work_keys_str_mv AT mohammadhaider developinganaipoweredalgorithmforautomateddetectionandclassificationofdentalcariesfromintraoralradiographsamachinelearningapproach