ArticleNPJ digital medicine2025
A general framework for governing marketed AI/ML medical devices.
Article 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 27 papers, 2 of them syntheses 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
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- An integrated AI-driven vaccine design process: a systematic review of workflows from generative design to translational prediction.Immunologic research · 2026Pooled it
- Ethical challenges in the algorithmic era: a systematic rapid review of risk insights and governance pathways for nursing predictive analytics and early warning systems.BMC medical ethics · 2025Pooled it
- Artificial intelligence in oncology: empowering clinicians for responsible integration.ESMO real world data and digital oncology · 2026Review
- Artificial intelligence and chatbots in general surgery: a survey among surgeons in Germany, Austria and Switzerland.Surgical endoscopy · 2026Article
- Translational bottlenecks in blood-based proteomics.EMBO molecular medicine · 2026Article
- Operationalizing the EU AI Act in a comprehensive cancer center through an institutional governance framework.NPJ digital medicine · 2026Review
- PROACTIVE-AI: An Intelligent Dashboard for Assessing and Predicting of FDA-approved AI Software Performance in Real-World Clinical Scenarios.Research square · 2026Article
- Artificial Intelligence and Clinician Burnout in the United States: A Narrative Review.Cureus · 2026Review
- Ethical Considerations in Personal Health Large Language Models.Journal of medical Internet research · 2026Article
- Nanostructured electrode materials and flexible-substrate engineering for wearable multi-analyte biosensors in diabetes monitoring and personalized care: a comprehensive review.Journal of materials science. Materials in medicine · 2026Review
- Artificial Intelligence in Gastrointestinal Endoscopy and Hemostatic Decision-Making: Current Evidence, Clinical Implications and Implementation Barriers.Life (Basel, Switzerland) · 2026Review
- The absence of full lifecycle risk management for AI-based medical devices in radiology.NPJ digital medicine · 2026Article
- Re: McCarthy et al: A Practical Guide to Evaluating Artificial Intelligence Imaging Models in Scientific Literature.Ophthalmology science · 2026Article
- The regulation of artificial intelligence in intensive care units: from narrow tools to generalist systems.NPJ digital medicine · 2026Review
- AI Competency: Current State and Challenges.JMIR medical education · 2026Article
- Scaling medical device regulatory science using large language models.NPJ digital medicine · 2026Article
- Multisite, External Validation of an AI-Enabled ECG Algorithm for Detection of Low Ejection Fraction.JACC. Advances · 2026Article
- Automated vertigo diagnosis using video-oculography and artificial intelligence for clinic-based triage: Preliminary results.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Research integrity and data ethics in AI-driven integrated healthcare: a critical appraisal.Frontiers in public health · 2026Review
- Article
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
Abstract
This project represents the first systematic assessment of the US Food and Drug Administration's postmarket surveillance of legally marketed artificial intelligence and machine learning based medical devices. We focus on the Manufacturer and User Facility Device Experience database-the FDA's central tool for tracking the safety of marketed AI/ML devices. In particular, we evaluate the data pertaining to adverse events associated with approximately 950 medical devices incorporating AI/ML functions for devices approved between 2010 through 2023, and we find that the existing system is insufficient for properly assessing the safety and effectiveness of AI/ML devices. In particular, we make three contributions: (1) characterize the adverse event reports for such devices, (2) examine the ways in which the existing FDA adverse reporting system for medical devices falls short, and (3) suggest changes FDA might consider in its approach to adverse event reporting for devices incorporating AI/ML functions.
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.