Evidence map›Paper›PMID 38089864›Full record

ReviewFrontiers in medicine2023

Defining medical liability when artificial intelligence is applied on diagnostic algorithms: a systematic review.

Clara Cestonaro, Arianna Delicati, Beatrice Marcante, Luciana Caenazzo, Pamela Tozzo

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 3 pooled it
–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

88 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Review
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  9. Ethical considerations in generative artificial intelligence for synthetic data generation in ophthalmology.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
    Review
  10. Strengths and Potential Pitfalls of the Use of Artificial Intelligence in Psychiatric Education and Practice.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026
    Article
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28 more citing papers are in PubMed but not listed here.

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

5 authors.

Clara CestonaroLegal Medicine Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy.
Arianna DelicatiLegal Medicine Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy.
Beatrice MarcanteLegal Medicine Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy.
Luciana CaenazzoLegal Medicine Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy.
Pamela TozzoLegal Medicine Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) in medicine is an increasingly studied and widespread phenomenon, applied in multiple clinical settings. Alongside its many potential advantages, such as easing clinicians' workload and improving diagnostic accuracy, the use of AI raises ethical and legal concerns, to which there is still no unanimous response. A systematic literature review on medical professional liability related to the use of AI-based diagnostic algorithms was conducted using the public electronic database PubMed selecting studies published from 2020 to 2023. The systematic review was performed according to 2020 PRISMA guidelines. The literature review highlights how the issue of liability in case of AI-related error and patient's damage has received growing attention in recent years. The application of AI and diagnostic algorithm moreover raises questions about the risks of using unrepresentative populations during the development and about the completeness of information given to the patient. Concerns about the impact on the fiduciary relationship between physician and patient and on the subject of empathy have also been raised. The use of AI in medical field and the application of diagnostic algorithms introduced a revolution in the doctor-patient relationship resulting in multiple possible medico-legal consequences. The regulatory framework on medical liability when AI is applied is therefore inadequate and requires urgent intervention, as there is no single and specific regulation governing the liability of various parties involved in the AI supply chain, nor on end-users. Greater attention should be paid to inherent risk in AI and the consequent need for regulations regarding product safety as well as the maintenance of minimum safety standards through appropriate updates.

Indexed as

artificial intelligencediagnostic algorithmmedical liabilityregulationsystematic review

Identifiers

PMID38089864
PMCPMC10711067

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.