Evidence map›Paper›PMID 41561651›Full record

ArticleFrontiers in transplantation2025

2024 transplant AI symposium: key AI models shaping the future of transplant care.

Annabel Koivu, Ghazal Azarfar, Saba Maleki, Aman Sidhu, Mamatha Bhat

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in transplantation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

5 authors.

Annabel KoivuDepartment of Medicine, University of Toronto, Toronto, ON, Canada.
Ghazal AzarfarTransplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada.
Saba MalekiTransplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada.
Aman SidhuDepartment of Medicine, University of Toronto, Toronto, ON, Canada.
Mamatha BhatTransplant AI Initiative, Ajmera Transplant Centre, University Health Network, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Experts in transplantation medicine and AI innovation came together to showcase advancements in AI applications with the potential to improve transplant outcomes. Ethical deployment, consolidation of multimodal data and supporting clinical decision making were among the themes addressed. Experts presented foundational models such as MedSAM for universal medical image segmentation, scPGT for single-cell genomics and Clinical Camel for clinical decision support, each demonstrating high capability and adaptability across transplant specialities. Experts highlighted future directions, considerations, and challenges for integrating these tools into clinical practice in an ethical and safe manner. We will summarize these themes as discussed at the Ajmera Transplant Centre's second annual Transplant AI Symposium.

Indexed as

artificial intelligence (AI)cardiac transplantliver transplantlung transplantsolid organ transplanttransplant

Identifiers

PMID41561651
PMCPMC12812975

What OpenQuestion holds

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Registered trials

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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.