Evidence map›Paper›PMID 42298876›Full record

ArticleSociology of health & illness2026

From Prediction to Horizon: Clinicians' Negotiations of AI-Driven Personal Prognoses in Clinical Practice.

Iben Mundbjerg Gjødsbøl, Mette Nordahl Svendsen

Abstract read
In one paragraph

Article in Sociology of health & illness, 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

2 authors.

Iben Mundbjerg GjødsbølCentre for Medical Science and Technology Studies, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0003-3938-5211
Mette Nordahl SvendsenCentre for Medical Science and Technology Studies, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0002-4777-4973

Funding

The independent Research Fund Denmark 10.46540/4302-00032B
6 · The paper itself

Abstract

Computational methods and tools under the label 'artificial intelligence' (AI) are increasingly promoted as solutions to the challenges of under-resourced and understaffed healthcare systems, with predictive modelling positioned as a means to improve efficiency and individualise care. Yet little is known about how predictive algorithms are taken up in the everyday practices of clinical decision-making. Drawing on ethnographic fieldwork with Danish cardiologists working with the CARDIA

Indexed as

Artificial IntelligenceClinical Decision-MakingNegotiatingAlgorithmsAnthropology, CulturalDenmarkHumansPrediction AlgorithmsPrognosisartificial intelligenceDenmarkethnographyhorizoningpredictive analyticsprognosis

Identifiers

PMID42298876
PMCPMC13270078

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.