ArticlePalliative medicine2026
Implementation of artificial intelligence in palliative and supportive care for people with cancer: A scoping review.
Article in Palliative medicine, 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.
- The Technologies, Applicability, and Trade-Offs of AI in Palliative Care for Older Adults: Scoping Review.Journal of medical Internet research · 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCancer remains a leading global health burden. Artificial intelligence offers new opportunities to address complex physical and psychological symptoms in palliative and supportive cancer care. Despite rapid advances, including large language models, these technologies have not been consistently reviewed in this context, highlighting a gap in the synthesised literature.
aimTo map current evidence on how artificial intelligence is implemented in palliative and supportive care for people with cancer and their caregivers, and to identify associated challenges and future directions.
designScoping review guided by the Joanna Briggs Institute (JBI) framework. DATA SOURCES: We searched PubMed, CENTRAL, PsycINFO, and CINAHL databases, along with grey literature, up to 17 September 2024, and manually screened reference lists.
resultsOf 2618 records screened, 199 studies were included. Most applications supported healthcare professionals, mainly for predictive purposes such as prognosis, symptom monitoring, and treatment-related adverse events. Machine learning was the predominant approach, reflecting reliance on structured clinical data. Publications increased markedly after 2020, with a sharp rise from 2022 onwards. Only 26 studies involved direct use by people with cancer or their caregivers, and large language model-based applications remained rare, indicating limited patient-facing use.
conclusionsArtificial intelligence is increasingly being applied in palliative and supportive care, yet applications designed for direct patient or caregiver use remain scarce. Further efforts should prioritise the development and validation of ethically sound, clinically integrated artificial intelligence tools to support person-centred palliative and supportive care.
Indexed as
Identifiers
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.