Evidence map›Paper›PMID 42487919›Full record

ArticleFrontiers in digital health2026

Assessing knowledge and perception of artificial intelligence in solid organ transplantation.

Lea Liaigre, Dorothee Lombardo, Marie-Camille Chaumais, Bruno Degano, Pierrick Bedouch, Sebastien Chanoine

Abstract read
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. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Lea LiaigrePharmacy Department, Grenoble Alpes University Hospital, Grenoble, France.
Dorothee LombardoPharmacy Department, Grenoble Alpes University Hospital, Grenoble, France.
Marie-Camille ChaumaisPharmacy Department, Assistance Publique - Hôpitaux de Paris (AP-HP), Hôpital Bicêtre, Le Kremlin-Bicêtre, France.
Bruno DeganoThorax and Vascular Department, Pneumology Clinic, Univ. Grenoble Alpes, Grenoble Alpes University Hospital, Grenoble, France.
Pierrick BedouchPharmacy Department, Grenoble Alpes University Hospital, Grenoble, France.
Sebastien ChanoinePharmacy Department, Grenoble Alpes University Hospital, Grenoble, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Artificial intelligence (AI) is increasingly integrated into healthcare, reshaping clinical decision-making and care pathways. In solid organ transplantation (SOT), where clinical complexity and uncertainty are high, AI holds particular promise. Yet, beyond technical performance, its successful adoption depends on how it is understood and perceived by patients and healthcare professionals (HP). To date, little is known about these perspectives in SOT. This study provides the first assessment of knowledge and perceptions of AI among patients and healthcare professionals in this field. Methods: A cross-sectional study was conducted among SOT patients and HP. Patients were recruited through associations, and HP through the French Society of Transplantation. Data were collected using a web-based questionnaire including open-ended and closed items addressing sociodemographic characteristics, declared knowledge, and perception of AI and its applications in healthcare and SOT. Thematic coding was used for qualitative data, regression models for association analyses, and reliability testing was assessed (Cronbach's α > 0.7). Results: 218 patients and 92 HP participated. Patients reported low AI declared knowledge (mean 2.4/10), while HP suggested slightly higher levels (3.8/10). 140 patients had heard of AI in healthcare, and very few were aware of its use in SOT ( Discussion: As declared knowledge was associated with perceptions of AI, these findings highlight the importance of targeted educational interventions to promote informed integration of AI in SOT. This exploratory study provides valuable insights into potential facilitators and barriers to adoption, providing actionable insights to guide implementation strategies and policy development in transplant care.

Indexed as

artificial intelligencecross-sectional studyknowledgeperceptionsolid organ transplantation

Identifiers

PMID42487919
PMCPMC13388862

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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.