Evidence map›Paper›PMID 40676176›Full record

ArticleCommunications engineering2025

Explainability in the age of large language models for healthcare.

Munib Mesinovic, Peter Watkinson, Tingting Zhu

Abstract read
In one paragraph

Article in Communications engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Artificial intelligence virtual bone organoids (AIVBOs).Journal of orthopaedic translation · 2026
    Review
  3. Article
  4. Causal graph neural networks for healthcare.Nature biomedical engineering · 2026
    Review
  5. Article
  6. Article
  7. Ethical Considerations in Personal Health Large Language Models.Journal of medical Internet research · 2026
    Article
  8. Article
  9. Integrating multi-omics data for next-generation cancer research and precision medicine.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  10. Article
  11. AI assistance in tumor multidisciplinary teams.ESMO real world data and digital oncology · 2026
    Review
  12. Article
  13. Article
  14. Article
  15. [Research progress and future prospects for artificial intelligence in the diagnosis and treatment of fatty liver disease].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025
    Review
  16. Benchmarking Foundation Models with Multimodal Public Electronic Health Records.IEEE journal of biomedical and health informatics · 2025
    Article
  17. Article
  18. Article
  19. Review
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

3 authors.

Munib MesinovicDepartment of Engineering Science, University of Oxford, Oxford, OX1 3PJ, UK. munib.mesinovic@eng.ox.ac.uk.ORCID http://orcid.org/0000-0003-3757-7877
Peter WatkinsonNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK.
Tingting ZhuDepartment of Engineering Science, University of Oxford, Oxford, OX1 3PJ, UK.ORCID http://orcid.org/0000-0002-1552-5630

Funding

Wellcome Trust
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Identifiers

PMID40676176
PMCPMC12271443

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.