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Use of artificial intelligence to assist dentists in diagnosing dental caries in radiographs in primary health care

Impact of using an artificial intelligence system in the radiographic diagnosis of caries lesions by primary healthcare dentists in Governador Valadares: a randomized experimental study

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
REBEC
Registry ID
RBR-7b39zbh
Enrollment
54
Registered
2026-03-23
Start date
2026-03-25
Completion date
Unknown
Last updated
2026-03-30

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Dental caries Dentists

Interventions

This is an experimental, randomized study, not blinded to the use of the intervention, maintaining partial blinding, since the dentists will be unaware of the reference standard results, the selection

Sponsors

Universidade Federal de Juiz de Fora Campus Governador Valadares
Lead Sponsor
Universidade Federal de Juiz de Fora Campus Governador Valadares
Collaborator

Eligibility

Inclusion criteria

Inclusion criteria: Dentists working in Primary Health Care in the municipality of Governador Valadares, Minas Gerais

Exclusion criteria

Exclusion criteria: Primary healthcare dentists who perform administrative functions; who have a specialization in radiology, or who are pursuing a specialization in radiology

Design outcomes

Primary

MeasureTime frame
The diagnostic accuracy of dentists in detecting caries lesions in interproximal radiographs is expected to be assessed through sensitivity, specificity, and area under the receiver operating characteristic curve, comparing evaluations performed with and without the aid of an artificial intelligence system, using micro-computed tomography as a reference standard

Secondary

MeasureTime frame
The time required to perform the radiographic diagnosis, measured in seconds, is expected to be determined during the evaluation of images in the intervention and control groups;It is expected to analyze intra- and inter-examiner agreement in the detection and classification of caries lesions, evaluated using the kappa coefficient or another appropriate statistical agreement coefficient;The aim is to determine the frequency of false positive and false negative results in the detection of caries lesions in interproximal radiographs by comparing assessments with and without the aid of artificial intelligence

Countries

BR

Contacts

Public ContactFrancielle Verner

Universidade Federal de Juiz de Fora Campus Governador Valadares

francielle.verner@ufjf.br+55 (33) 3301-1000 Ramal 1524

Outcome results

None listed

Source: REBEC (via WHO ICTRP) · Data processed: Apr 4, 2026