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dc.contributor.authorDevlin, Hugh
dc.contributor.authorWilliams, Tomos; email: tomos.williams@manchester.ac.uk
dc.contributor.authorGraham, Jim
dc.contributor.authorAshley, Martin
dc.date.accessioned2021-10-22T15:49:59Z
dc.date.available2021-10-22T15:49:59Z
dc.date.issued2021-10-22
dc.date.submitted2020-10-20
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/626161/41415_2021_Article_3526_nlm.xml?sequence=2
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/626161/41415_2021_Article_3526.pdf?sequence=3
dc.identifier.citationBritish Dental Journal, volume 231, issue 8, page 481-485
dc.identifier.urihttp://hdl.handle.net/10034/626161
dc.descriptionFrom Springer Nature via Jisc Publications Router
dc.descriptionHistory: received 2020-10-20, accepted 2020-12-16, registration 2021-01-01, pub-print 2021-10, pub-electronic 2021-10-22, online 2021-10-22
dc.descriptionPublication status: Published
dc.description.abstractAbstract: Introduction Reversal of enamel-only proximal caries by non-invasive treatments is important in preventive dentistry. However, detecting such caries using bitewing radiography is difficult and the subtle patterns are often missed by dental practitioners. Aims To investigate whether the ability of dentists to detect enamel-only proximal caries is enhanced by the use of AssistDent artificial intelligence (AI) software. Materials and methods In the ADEPT (AssistDent Enamel-only Proximal caries assessmenT) study, 23 dentists were randomly divided into a control arm, without AI assistance, and an experimental arm, in which AI assistance provided on-screen prompts indicating potential enamel-only proximal caries. All participants analysed a set of 24 bitewings in which an expert panel had previously identified 65 enamel-only carious lesions and 241 healthy proximal surfaces. Results The control group found 44.3% of the caries, whereas the experimental group found 75.8%. The experimental group incorrectly identified caries in 14.6% of the healthy surfaces compared to 3.7% in the control group. The increase in sensitivity of 71% and decrease in specificity of 11% are statistically significant (p <0.01). Conclusions AssistDent AI software significantly improves dentists' ability to detect enamel-only proximal caries and could be considered as a tool to support preventive dentistry in general practice.
dc.languageen
dc.publisherNature Publishing Group UK
dc.rightsLicence for this article: http://creativecommons.org/licenses/by/4.0/
dc.sourcepissn: 0007-0610
dc.sourceeissn: 1476-5373
dc.subjectResearch
dc.subjectresearch
dc.titleThe ADEPT study: a comparative study of dentists' ability to detect enamel-only proximal caries in bitewing radiographs with and without the use of AssistDent artificial intelligence software
dc.typearticle
dc.date.updated2021-10-22T15:49:59Z
dc.date.accepted2020-12-16


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