Evidence map›Paper›PMID 42027212›Full record

ArticleFrontiers in digital health2026

Medical clinical minds meet artificial intelligence: Italian physicians' knowledge, attitudes, and concordance between Italian physicians and AI-generated diagnoses. A national cross-sectional study.

Vincenza Cofini, Mario Muselli, Laura Piccardi, Eugenio Benvenuti, Ginevra Di Pangrazio, Martina Mancinelli, Eleonora Cimino, Patrizia Palermo, Emiliano Petrucci, Giovanna Picchi and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

17 authors.

Vincenza CofiniDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Mario MuselliDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Laura PiccardiDepartment of Psychology, Sapienza University of Rome, Rome, Italy.
Eugenio BenvenutiDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Ginevra Di PangrazioDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Martina MancinelliScienze Anatomiche, Istologiche, Medico Legali E Dell'apparato Locomotore, Sapienza University, Rome, Italy.
Eleonora CiminoDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Patrizia PalermoDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Emiliano PetrucciDepartment of Anesthesia and Intensive Care Unit, San Salvatore Academic Hospital of L'Aquila, L'Aquila, Italy.
Giovanna PicchiDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Loreta TobiaDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Arcangelo BarbonettiDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Giovambattista DesideriDepartment of Clinical, Internal Medicine, Anesthesiological and Cardiovascular Sciences, Sapienza University, Rome, Italy.
Leila FabianiDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Maurizio GuidoDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Franco MarinangeliDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Stefano NecozioneDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial Intelligence has increasingly been integrated into clinical practice, yet its adoption and perception among medical professionals remain poorly understood, particularly in the Italian healthcare system. To investigate Italian physicians' knowledge, attitudes, and clinical concordance with AI-generated diagnostic recommendations, using a validated questionnaire and a clinical scenario processed by ChatGPT. Methods: A national, cross-sectional web-based survey was conducted among 587 Italian physicians using an online validated questionnaire. The first part of the questionnaire assessed self-reported knowledge, prior experience, attitudes, and willingness to adopt AI in medicine. The second part assessed clinical concordance between AI proposals and physicians about clinical cases evaluated by ChatGPT. Results: Most participants reported basic AI knowledge ( Conclusion: Italian physicians showed a strong interest in adopting AI tools, despite significant knowledge gaps and limited practical experience. The high concordance between physicians' evaluations and ChatGPT's diagnostic insights suggests potential for AI-based decision support in clinical workflows. Targeted training and institutional support are essential to bridge the gap between enthusiasm and readiness for AI integration.

Indexed as

artificial intelligenceChatGPTclinical decision supportdiagnostic concordancedigital healthItalymedical educationphysicians

Identifiers

PMID42027212
PMCPMC13099893

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.