ArticleJournal of clinical medicine2022
Patients' Perspectives on Artificial Intelligence in Dentistry: A Controlled Study.
Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Barriers and Facilitators to Patient Acceptance of Artificial Intelligence in Health Care: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Trust in Artificial Intelligence-Generated Oral Health Information and Its Influence on Patient Decision-Making: A Cross-Sectional Study.Oral health & preventive dentistry · 2026Article
- Artificial Intelligence in Oral and Maxillofacial Surgery-A Narrative Review.Journal of clinical medicine · 2026Review
- Constructs Influencing Patient Perceptions of Use of AI in Medical Imaging Analysis: Systematic Review.Interactive journal of medical research · 2026Review
- Use of artificial intelligence in oral radiology: a multicenter cross-sectional study in Egypt.BMC oral health · 2025Observational
- Artificial intelligence in dentistry: awareness among dentists and computer scientists.Oral radiology · 2025Article
- A Comparison of Deep Learning vs. Dental Implantologists in Cone-Beam Computed Tomography-Based Bone Quality Classification.Journal of imaging informatics in medicine · 2025Article
- Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation.Journal of participatory medicine · 2025Article
- Artificial intelligence in dentistry: insights and expectations from Swiss dental professionals.BMC medical informatics and decision making · 2025Article
- The Validation of an Artificial Intelligence-Based Software for the Detection and Numbering of Primary Teeth on Panoramic Radiographs.Diagnostics (Basel, Switzerland) · 2025Article
- Article
- The relationships of personality traits on perceptions and attitudes of dentistry students towards AI.BMC medical education · 2025Article
- Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists.Oral radiology · 2025Article
- Acceptability of artificial intelligence in dental radiology among patients in India: are we ready for this revolution?Oral radiology · 2025Article
- Artificial intelligence-produced radiographic enhancements in dental clinical care: provider and patient perspectives.Frontiers in oral health · 2025Article
- Exploring trust factors in AI-healthcare integration: a rapid review.Frontiers in artificial intelligence · 2025Review
- Race to the Moon or the Bottom? Applications, Performance, and Ethical Considerations of Artificial Intelligence in Prosthodontics and Implant Dentistry.Dentistry journal · 2024Review
- Artificial Intelligence in Orthodontics: Critical Review.Journal of dental research · 2024Review
- Perceptiveness and Attitude on the use of Artificial Intelligence (AI) in Dentistry among Dentists and Non-Dentists - A Regional Survey.Journal of pharmacy & bioallied sciences · 2024Article
- Patient Perspectives on the Use of Artificial Intelligence in Health Care: A Scoping Review.Journal of patient-centered research and reviews · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: As artificial intelligence (AI) becomes increasingly important in modern dentistry, we aimed to assess patients’ perspectives on AI in dentistry specifically for radiographic caries detection and the impact of AI-based diagnosis on patients’ trust. Methods: Validated questionnaires with Likert-scale batteries (1: “strongly disagree” to 5: “strongly agree”) were used to query participants’ experiences with dental radiographs and their knowledge/attitudes towards AI as well as to assess how AI-based communication of a diagnosis impacted their trust, belief, and understanding. Analyses of variance and ordinal logistic regression (OLR) were used (p < 0.05). Results: Patients were convinced that “AI is useful” (mean Likert ± standard deviation 4.2 ± 0.8) and did not fear AI in general (2.2 ± 1.0) nor in dentistry (1.6 ± 0.8). Age, education, and employment status were significantly associated with patients’ attitudes towards AI for dental diagnostics. When shown a radiograph with a caries lesion highlighted by an arrow, patients recognized the lesion significantly less often than when using AI-generated coloured overlays highlighting the lesion (p < 0.0005). AI-based communication did not significantly affect patients’ trust in dentists’ diagnosis (p = 0.44; OLR). Conclusions: Patients showed a positive attitude towards AI in dentistry. AI-supported diagnostics may assist communicating radiographic findings by increasing patients’ ability to recognize caries lesions on dental radiographs.
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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.