Evidence map›Paper›PMID 39176474›Full record

ReviewOral diseases2025

The risks of artificial intelligence: A narrative review and ethical reflection from an Oral Medicine group.

Qingmei Joy Feng, Molly Harte, Barbara Carey, Ali Alqarni, Luis Monteiro, Márcio Diniz-Freitas, Jean-Cristophe Fricain, Giovanni Lodi, Vlaho Brailo, Mattia Andreoletti and 1 more

Abstract readReview
In one paragraph

Review in Oral diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Adverse Oral Mucosal Reaction to Sublingual Captopril: A Case Report With Exploratory Insights Into AI-Assisted Clinical Reasoning.Special care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Qingmei Joy FengOral Medicine, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Molly HarteOral Medicine, Guy's and St Thomas' NHS Foundation Trust, London, UK.ORCID 0000-0001-8457-6792
Barbara CareyDepartment of Head and Neck Surgical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Ali AlqarniDepartment of Oral & Maxillofacial Surgery and Diagnostic Sciences, Faculty of Dentistry, Taif University, Taif, Saudi Arabia.ORCID 0000-0001-9997-8292
Luis MonteiroMedicine and Oral Surgery Department, University Institute of Health Sciences (IUCS), UNIPRO, CESPU, Gandra, Portugal.
Márcio Diniz-FreitasSpecial Care Dentistry Unit, School of Medicine and Dentistry, University Santiago de Compostela, Santiago de Compostela, Spain.ORCID 0000-0001-5349-1091
Jean-Cristophe FricainOral Surgery Department, University of Bordeaux, Bordeaux, France.
Giovanni LodiDipartimento di Scienze Biomediche, Chirurgiche e Odontoiatriche, Università Degli Studi di Milano, Milan, Italy.
Vlaho BrailoSchool of Dental Medicine, University of Zagreb, Zagreb, Croatia.ORCID 0000-0002-8449-871X
Mattia AndreolettiDepartment of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.ORCID 0000-0003-1880-0770
Rui AlbuquerqueOral Medicine, Guy's and St Thomas' NHS Foundation Trust, London, UK.ORCID 0000-0002-1741-8871

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a relatively new tool, the use of artificial intelligence (AI) in medicine and dentistry has the potential to significantly transform the healthcare sector. AI has already demonstrated efficacy in medical diagnosis across several specialties, used successfully to detect breast, lung and skin cancer. In Oral Medicine, AI may be applied in a similar fashion, used in the detection and diagnosis of oral cancers and oral potentially malignant diseases. Despite its promise as a transformative diagnostic aid, the use of AI in healthcare presents significant safety, reliability and ethical concerns. There is no formal consensus on the safe and ethical implementation of AI systems in healthcare settings, but the literature converges on several key principles of ethical AI use including transparency, justice and fairness, non-maleficence, responsibility and privacy. This article provides a narrative review of the key ethical issues surrounding AI use in medicine, and reflects on these, providing view-points of a bioethicist and Oral Medicine clinicians from several units.

Indexed as

Artificial IntelligenceOral MedicineHumansMouth Neoplasmsartificial intelligencedentistryethics

Identifiers

PMID39176474
PMCPMC11976142

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.