ArticleFuture healthcare journal2026
Recognising dying: Will artificial intelligence (AI) help improve clinical accuracy?
Article in Future healthcare journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Everybody's business: insights into palliative and end-of-life care for clinicians who treat mortals (yes, that means you).Future healthcare journal · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The number of people requiring palliative care in the UK is projected to rise significantly, creating an urgent need for earlier and more systematic recognition of those approaching the end of life. Current clinical markers and tools for predicting prognosis are limited in their accuracy, and prone to human and systemic biases. Artificial intelligence (AI) offers potential to improve prediction of deterioration and dying, and early studies suggest that it may support timely interventions and advance care planning. However, integration of AI must prioritise data integrity, accountability and minimising the amplification of existing inequities. Crucially, recognising dying remains a fundamentally human task with ethical, relational and existential dimensions that AI cannot replicate. Successful implementation will depend on thoughtful human-AI collaboration that strengthens clinical insight without compromising the compassionate, person-centred approach that is central to palliative care.
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What OpenQuestion holds
Registered trials
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.