ArticleBMC medical informatics and decision making2025
Human-centered AI in healthcare: empowering patients and support persons in clinical decision-making.
Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- From interface to outcome: a 4I framework for AI-linked functionality in electronic health records.BMC medical informatics and decision making · 2026Pooled it
- A lifecycle governance and learning health system framework for trustworthy, generalizable, and sustainable human-ai partnership in clinical practice: Lessons from the asthma-guidance and prediction system (A-GPS).Journal of the National Medical Association · 2026Review
- Artificial Intelligence for Personalized Management of Acute Myeloid Leukemia.Journal of personalized medicine · 2026Review
- The Design-Driven Innovation Path of Human-Centered Artificial Intelligence in the Field of Healthcare: Theory, Practice, and Future Prospects.Healthcare (Basel, Switzerland) · 2026Review
- Human-AI Interaction in Kidney Transplant Decision Support Systems: Qualitative Study of Patient and Support Person Expectations.Journal of medical Internet research · 2026Article
- Closing the loop: human-augmented, mechanistically enhanced AI for proactive management of drug-drug interactions.Frontiers in pharmacology · 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
11 authors.
Funding
Abstract
Artificial intelligence (AI) has emerged as a promising tool to enhance medical practice and improve patient outcomes. However, introducing AI in interactions between patients, support persons (SPs) and physicians may create real or perceived information asymmetries and may not always be well accepted by end-users. To ensure that AI contributes to patient empowerment rather than undermining it, there is a need to better understand how AI-based tools affect communication, trust and decision-making in clinical encounters. Research should focus on identifying how AI can support patients' autonomy, trust and acceptance, how it may strengthen the role of SPs and promote transparent and ethically sound care. With these findings, applying a human-centered design with established technology acceptance frameworks (e.g. TAM, UTAUT) will be crucial to guide evidence-based implementation. Only by involving patients, SPs and physicians in AI development can these technologies unfold their full potential to deliver equitable, interpretable and patient-centered healthcare.
Indexed as
Identifiers
What Socratic 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 Socratic graph.