ArticleBDJ open2025
Ethical insights into AI-driven caries detection: a scoping review.
Article in BDJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial Intelligence (AI) has become increasingly integrated into dental diagnostics, particularly for detecting carious lesions. While AI offers benefits such as improved accuracy and efficiency, its use raises important ethical concerns, including transparency, patient privacy, autonomy, diversity and accountability. This scoping review aims to identify these ethical concerns using a structured ethical framework. METHODOLOGY: Three databases were searched for papers regarding caries detection using AI. An established ethical framework was used to screen each paper for potential areas of concern.
resultsA total of 351 abstracts were screened, of which 7 articles were included in this review. Each article was screened for established ethical principles including transparency, diversity, wellness, autonomy, privacy, accountability, equity, prudence, sustainable development, solidarity and governance. Diversity was the main ethical concern. Concerns related to accountability, equity and transparency were identified in 2 of the articles whereas ethical issue of privacy was identified in 4 of the articles. Only one study mentioned that no ethical approval was taken prior to commencement of study.
conclusionAI in caries detection faces ethical issues like data bias, privacy risks, and equity concerns, potentially leading to flawed AI models. These issues can be addressed by creating a more specialized ethical framework that is specific to AI in dentistry. CLINICAL RELEVANCE: Understanding ethical challenges in AI-driven caries detection is critical to ensure accurate diagnostics, maintain patient trust, protect privacy, and support informed decision-making. Clinicians must be equipped to navigate these challenges as AI tools become more prevalent in dental practice.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.