Abstract
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, twenty-three 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® Artificial Intelligence 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.
Original language | English |
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Pages (from-to) | 481–485 |
Journal | British Dental Journal |
Volume | 231 |
Early online date | 22 Oct 2021 |
DOIs | |
Publication status | Published - 22 Oct 2021 |
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Dive into the research topics of 'The 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'. Together they form a unique fingerprint.Impacts
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Producing innovative diagnostic software/products for the earlier identification of dental decay and other potential problems (Spin out company Manchester Imaging Ltd)
Devlin, H. (Corresponding participant), Horner, K. (Participant) & Graham, J. (Participant)
Impact: Health and wellbeing, Technological, Economic