File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Characteristics, licensing, and ethical considerations of openly accessible oral-maxillofacial imaging datasets: a systematic review

TitleCharacteristics, licensing, and ethical considerations of openly accessible oral-maxillofacial imaging datasets: a systematic review
Authors
Issue Date5-Jul-2025
PublisherNature Research
Citation
npj Digital Medicine, 2025, v. 8 How to Cite?
Abstract

Several open-source oral-maxillofacial imaging datasets have been created but their characteristics, ethical clearance, and licensing for reuse remain unclear. This study aimed to systematically identify these datasets and investigate their characteristics, ethical approvals, and licensing requirements for reuse. Open-source oral-maxillofacial imaging datasets were identified through electronic databases and dataset platforms. 105 datasets with 437538 images and 100 intraoral videos from patients across twenty-one countries were included. The datasets comprise imaging modalities, including photographs, periapical, panoramic, and cephalometric radiographs, CBCT, MRI, surface scans, videos, and histopathological images. Nearly 80% of them provide annotations, but only 25.7% specified the annotators' qualification. The majority (83.8%) did not disclose whether ethical approval was obtained, while 61.9% specified terms or licenses for dataset reuse. There is an urgent need to develop standardized guidelines for reusing image datasets and to establish AI-specific consents to fully inform patients about potential uses of their data in AI projects.


Persistent Identifierhttp://hdl.handle.net/10722/357840
ISSN
2023 Impact Factor: 12.4
2023 SCImago Journal Rankings: 4.273
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHao, Jing-
dc.contributor.authorNalley, Andrew-
dc.contributor.authorYeung, Andy Wai Kan-
dc.contributor.authorTanaka, Ray-
dc.contributor.authorAi, Qi Yong H-
dc.contributor.authorLam, Walter Yu Hang-
dc.contributor.authorShan, Zhiyi-
dc.contributor.authorLeung, Yiu Yan-
dc.contributor.authorAlHadidi, Abeer-
dc.contributor.authorBornstein, Michael M-
dc.contributor.authorTsoi, James Kit Hon-
dc.contributor.authorMcGrath, Colman-
dc.contributor.authorHung, Kuo Feng-
dc.date.accessioned2025-07-22T03:15:16Z-
dc.date.available2025-07-22T03:15:16Z-
dc.date.issued2025-07-05-
dc.identifier.citationnpj Digital Medicine, 2025, v. 8-
dc.identifier.issn2398-6352-
dc.identifier.urihttp://hdl.handle.net/10722/357840-
dc.description.abstract<p>Several open-source oral-maxillofacial imaging datasets have been created but their characteristics, ethical clearance, and licensing for reuse remain unclear. This study aimed to systematically identify these datasets and investigate their characteristics, ethical approvals, and licensing requirements for reuse. Open-source oral-maxillofacial imaging datasets were identified through electronic databases and dataset platforms. 105 datasets with 437538 images and 100 intraoral videos from patients across twenty-one countries were included. The datasets comprise imaging modalities, including photographs, periapical, panoramic, and cephalometric radiographs, CBCT, MRI, surface scans, videos, and histopathological images. Nearly 80% of them provide annotations, but only 25.7% specified the annotators' qualification. The majority (83.8%) did not disclose whether ethical approval was obtained, while 61.9% specified terms or licenses for dataset reuse. There is an urgent need to develop standardized guidelines for reusing image datasets and to establish AI-specific consents to fully inform patients about potential uses of their data in AI projects.<br></p>-
dc.languageeng-
dc.publisherNature Research-
dc.relation.ispartofnpj Digital Medicine-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleCharacteristics, licensing, and ethical considerations of openly accessible oral-maxillofacial imaging datasets: a systematic review-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1038/s41746-025-01818-5-
dc.identifier.volume8-
dc.identifier.eissn2398-6352-
dc.identifier.isiWOS:001522799800004-
dc.identifier.issnl2398-6352-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats