ReviewPET clinics2021
Equitable Implementation of Artificial Intelligence in Medical Imaging: What Can be Learned from Implementation Science?
Review in PET clinics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Behavioral and Engagement Predictors of Arthroplasty Clinic No-Shows: A Calibrated Machine Learning Analysis.Arthroplasty today · 2026Article
- Findings from the 2025 AMCP Foundation Symposium: Health Optimization 2.0.Journal of managed care & specialty pharmacy · 2026Article
- Bridging Health Disparities in the Data-Driven World of Artificial Intelligence: A Narrative Review.Journal of racial and ethnic health disparities · 2025Review
- Exploring the complex nature of implementation of Artificial intelligence in clinical practice: an interview study with healthcare professionals, researchers and Policy and Governance Experts.PLOS digital health · 2025Article
- Implementation Strategy for Artificial Intelligence in Radiotherapy: Can Implementation Science Help?JCO clinical cancer informatics · 2024Article
- Diagnostic accuracy of an artificial intelligence algorithm versus radiologists for fracture detection on cervical spine CT.European radiology · 2024Article
- Achieving large-scale clinician adoption of AI-enabled decision support.BMJ health & care informatics · 2024Article
- Advancing healthcare equity through dissemination and implementation science.Health services research · 2023Review
- Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2023Article
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
Abstract
Artificial intelligence (AI) has been rapidly adopted in various health care domains. Molecular imaging, accordingly, has demonstrated growing academic and commercial interest in AI. Unprepared and inequitable implementation and scale-up of AI in health care may pose challenges. Implementation of AI, as a complex intervention, may face various barriers, at individual, interindividual, organizational, health system, and community levels. To address these barriers, recommendations have been developed to consider health equity as a critical lens to sensitize implementation, engage stakeholders in implementation and evaluation, recognize and incorporate the iterative nature of implementation, and integrate equity and implementation in early-stage AI research.
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.