Evidence map›Paper›PMID 42320913›Full record

ArticleBMJ health & care informatics2026

Missing infrastructure for real-world predictive AI impact.

Benjamin I Perry, Ben Hammond, Dominic Oliver, Ashley Mushambi, Carina Andrews, Niels Peek, Ben Van Calster, Laure Wynants, Annabel E L Walsh, Joseph E Alderman and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ health & care informatics, 2026. 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

14 authors.

Benjamin I PerryInstitute for Mental Health, University of Birmingham, Birmingham, UK b.i.perry@bham.ac.uk.ORCID http://orcid.org/0000-0002-1533-026X
Ben HammondApplied Health Sciences, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0001-9928-6843
Dominic OliverDepartment of Psychiatry, University of Oxford, Oxford, UK.
Ashley MushambiExpert by Experience, NA, UK.
Carina AndrewsExpert by Experience, NA, UK.
Niels PeekTHIS Institute, University of Cambridge, UK.ORCID http://orcid.org/0000-0002-6393-9969
Ben Van CalsterDepartment of Development and Regeneration, Katholieke Universiteit Leuven, Leuven, Flanders, Belgium.
Laure WynantsCare and Public Health Research Institute, Maastricht University, Maastricht, Limburg, Netherlands.
Annabel E L WalshThe McPin Foundation, London, UK.
Joseph E AldermanInflammation and Ageing, University of Birmingham College of Medical and Dental Sciences, Birmingham, UK.
Shuqing SiInstitute for Mental Health, University of Birmingham, Birmingham, UK.
Alastair K DennistonInflammation and Ageing, University of Birmingham College of Medical and Dental Sciences, Birmingham, UK.
Simon J GriffinPublic Health and Primary Care, University of Cambridge, Cambridge, UK.
Joie EnsorApplied Health Sciences, University of Birmingham, Birmingham, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health systems are under increasing pressure as chronic disease becomes the dominant burden of care. Addressing this requires earlier detection and prevention, and predictive artificial intelligence (AI) tools are a demonstrable means of targeting interventions more effectively. Despite extensive research activity and substantial public funding, few predictive AI tools are translated effectively into routine care. We argue that the primary translational barrier is now organisational rather than solely methodological: without defined institutional ownership and long-term stewardship, including to support obtaining and maintaining regulatory certification and navigating governance structures, predictive AI tools cannot progress beyond print. Three interdependent recommendations are proposed to address this problem.

Indexed as

Artificial IntelligenceHumansPrediction AlgorithmsArtificial intelligenceClinical GovernanceData ScienceImplementation Science

Identifiers

PMID42320913
PMCPMC13288887

What Socratic 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 Socratic graph.