ReviewNPJ digital medicine2025
Examining human-AI interaction in real-world healthcare beyond the laboratory.
Review in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Google Translate Voice App vs. Qualified Interpreters: An Exploratory Study of Clinical Accuracy in Real-World Speech/Voice Encounters.Healthcare (Basel, Switzerland) · 2026Article
- Review
- Article
- Governing Patient-Facing AI-Generated Video in Digital Health: A Risk-and-Ethics Matrix for Deployment, Monitoring, and Change Control.Journal of medical Internet research · 2026Article
- Blocking the Reflection: Milestones and Hurdles for Digital Twins in Mental Health.Pharmacopsychiatry · 2026Review
- Comparing artificial intelligence and healthcare professional performance in surgical and interventional video analysis: a systematic review and meta-analysis.NPJ digital medicine · 2026Article
- Collaborative and Cooperative Hospital "In-House" Medical Device Development and Implementation in the AI Age: The European Responsible AI Development (EURAID) Framework Compatible With European Values.Journal of medical Internet research · 2026Article
- Human-large language model collaboration in clinical medicine: a systematic review and meta-analysis.NPJ digital medicine · 2026Article
- Enabling Just-in-Time Clinical Oncology Analysis With Large Language Models: Feasibility and Validation Study Using Unstructured Synthetic Data.JMIR medical informatics · 2025Article
- Large language models for clinical decision support in gastroenterology and hepatology.Nature reviews. Gastroenterology & hepatology · 2025Review
- Methodological Challenges in Deep Learning-Based Detection of Intracranial Aneurysms: A Scoping Review.Neurointervention · 2025Review
- Young Adult Perspectives on Artificial Intelligence-Based Medication Counseling in China: Discrete Choice Experiment.Journal of medical Internet research · 2025Article
- Designing AI tools to advance health equity in resource-constrained low- and middle-income countries.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) is revolutionizing healthcare, but its true impact depends on seamless human interaction. While most research focuses on technical metrics, we lack frameworks to measure the compatibility or synergy of real-world human-AI interactions in healthcare settings. We propose a multimodal toolkit combining ecological momentary assessment, quantitative observations, and baseline measurements to optimize AI implementation.
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.