ReviewCureus2025
The Use of Artificial Intelligence in Palliative Care Communication: A Narrative Review.
Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- The Technologies, Applicability, and Trade-Offs of AI in Palliative Care for Older Adults: Scoping Review.Journal of medical Internet research · 2026Article
- Exploring the application of Artificial Intelligence in palliative care and its practical, technical and ethical considerations: a scoping review.BMC palliative care · 2026Article
- "Black box" artificial intelligence for mortality prediction: a mixed-methods study of palliative care team, patient, and caregiver perspectives.Annals of palliative medicine · 2026Article
- Impact of Artificial Intelligence on the Care of Terminally Ill Patients.Healthcare (Basel, Switzerland) · 2026Review
- Digital storytelling as a memory-making intervention for children and families in paediatric palliative care in Ireland: an adaptation study.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Technological advances, such as "machine learning" and "natural language processing," have enabled systems and machines to perform complex tasks that previously required human intervention. Artificial intelligence (AI) has emerged as one of the most significant advancements in the healthcare sector, playing a key role in the evolution of palliative care (PC). Our main objective was to explore how AI can improve the quality of communication in decision-making in PC. A narrative review was conducted to obtain an interpretative synthesis and a comprehensive perspective on the subject under analysis. The research was carried out using the terms "Palliative Care," "Communication," "Artificial Intelligence," "Forecasting" and "Decision Making." Nine articles were included in the study, and after data analysis under Jean Watson's Theory of Transpersonal Caring, four categories were defined that respond to the proposed objective: person-centred care and authentic relationships, decision support based on individualised knowledge, facilitation of transparent communication and advanced care planning, promotion of a healing environment and emotional well-being and education of health professionals and critical reflection. As a result, we identified the need for a multifaceted approach, involving the continuous validation of models, proper training of healthcare professionals and engagement of individuals in decision-making processes. This ensures that decisions are grounded in robust evidence and ethical principles, making sure that AI acts as a true ally rather than a source of additional risks. In conclusion, AI can effectively be a valuable support tool in decision-making, but it is crucial that professionals remain aware of its limitations and can apply critical judgment in each situation.
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.