ArticleFrontiers in medicine2025
Who moved my scan? Early adopter experiences with pre- and post-market healthcare AI regulation challenges.
Article in Frontiers in medicine, 2025. 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.
- Continuous assurance for AI-driven clinical decision support systems.Frontiers in artificial intelligence · 2026Review
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
Real-world clinical experience provides a much-needed opportunity for deep learning AI algorithms to evolve and improve. Yet, it also constitutes a regulatory challenge, since such potential for learning may essentially change the algorithm and introduce new biases. We focus on the gaps between "lifecycle" regulation and implementation from the perspective of the deployers, addressing three interconnected dimensions: (a) How precautionary regulation affects AI deployment in healthcare, (b) How healthcare providers view explainable AI (XAI), and (c) How AI deployment influences, and is influenced by, team routines in clinical settings. We conclude by suggesting ways in which the ends of healthcare AI regulation and deployment can successfully meet.
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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.