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Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis
PURPOSE: The aim of this study was to conduct a scoping review and meta-analysis to provide overall estimates of the recall and precision of artificial intelligence for detection and segmentation using oral and maxillofacial cone-beam computed tomography (CBCT) scans. MATERIALS AND METHODS: A litera...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Academy of Oral and Maxillofacial Radiology
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10315225/ https://www.ncbi.nlm.nih.gov/pubmed/37405196 http://dx.doi.org/10.5624/isd.20220224 |
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author | Abesi, Farida Maleki, Mahla Zamani, Mohammad |
author_facet | Abesi, Farida Maleki, Mahla Zamani, Mohammad |
author_sort | Abesi, Farida |
collection | PubMed |
description | PURPOSE: The aim of this study was to conduct a scoping review and meta-analysis to provide overall estimates of the recall and precision of artificial intelligence for detection and segmentation using oral and maxillofacial cone-beam computed tomography (CBCT) scans. MATERIALS AND METHODS: A literature search was done in Embase, PubMed, and Scopus through October 31, 2022 to identify studies that reported the recall and precision values of artificial intelligence systems using oral and maxillofacial CBCT images for the automatic detection or segmentation of anatomical landmarks or pathological lesions. Recall (sensitivity) indicates the percentage of certain structures that are correctly detected. Precision (positive predictive value) indicates the percentage of accurately identified structures out of all detected structures. The performance values were extracted and pooled, and the estimates were presented with 95% confidence intervals (CIs). RESULTS: In total, 12 eligible studies were finally included. The overall pooled recall for artificial intelligence was 0.91 (95% CI: 0.87-0.94). In a subgroup analysis, the pooled recall was 0.88 (95% CI: 0.77-0.94) for detection and 0.92 (95% CI: 0.87-0.96) for segmentation. The overall pooled precision for artificial intelligence was 0.93 (95% CI: 0.88-0.95). A subgroup analysis showed that the pooled precision value was 0.90 (95% CI: 0.77-0.96) for detection and 0.94 (95% CI: 0.89-0.97) for segmentation. CONCLUSION: Excellent performance was found for artificial intelligence using oral and maxillofacial CBCT images. |
format | Online Article Text |
id | pubmed-10315225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Korean Academy of Oral and Maxillofacial Radiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-103152252023-07-03 Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis Abesi, Farida Maleki, Mahla Zamani, Mohammad Imaging Sci Dent Review Article PURPOSE: The aim of this study was to conduct a scoping review and meta-analysis to provide overall estimates of the recall and precision of artificial intelligence for detection and segmentation using oral and maxillofacial cone-beam computed tomography (CBCT) scans. MATERIALS AND METHODS: A literature search was done in Embase, PubMed, and Scopus through October 31, 2022 to identify studies that reported the recall and precision values of artificial intelligence systems using oral and maxillofacial CBCT images for the automatic detection or segmentation of anatomical landmarks or pathological lesions. Recall (sensitivity) indicates the percentage of certain structures that are correctly detected. Precision (positive predictive value) indicates the percentage of accurately identified structures out of all detected structures. The performance values were extracted and pooled, and the estimates were presented with 95% confidence intervals (CIs). RESULTS: In total, 12 eligible studies were finally included. The overall pooled recall for artificial intelligence was 0.91 (95% CI: 0.87-0.94). In a subgroup analysis, the pooled recall was 0.88 (95% CI: 0.77-0.94) for detection and 0.92 (95% CI: 0.87-0.96) for segmentation. The overall pooled precision for artificial intelligence was 0.93 (95% CI: 0.88-0.95). A subgroup analysis showed that the pooled precision value was 0.90 (95% CI: 0.77-0.96) for detection and 0.94 (95% CI: 0.89-0.97) for segmentation. CONCLUSION: Excellent performance was found for artificial intelligence using oral and maxillofacial CBCT images. Korean Academy of Oral and Maxillofacial Radiology 2023-06 2023-03-24 /pmc/articles/PMC10315225/ /pubmed/37405196 http://dx.doi.org/10.5624/isd.20220224 Text en Copyright © 2023 by Korean Academy of Oral and Maxillofacial Radiology https://creativecommons.org/licenses/by-nc/3.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0 (https://creativecommons.org/licenses/by-nc/3.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Abesi, Farida Maleki, Mahla Zamani, Mohammad Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis |
title | Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis |
title_full | Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis |
title_fullStr | Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis |
title_full_unstemmed | Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis |
title_short | Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis |
title_sort | diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: a scoping review and meta-analysis |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10315225/ https://www.ncbi.nlm.nih.gov/pubmed/37405196 http://dx.doi.org/10.5624/isd.20220224 |
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