Evidence map›Paper›PMID 42082591›Full record

ArticleNPJ digital medicine2026

The absence of full lifecycle risk management for AI-based medical devices in radiology.

Jia Li, Zicong Guo, Yi Guo, Rui Xiao, Yuxiao Ding, Wenjie Shi, Wei Liu

Abstract read
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jia LiSchool of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
Zicong GuoSchool of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
Yi GuoSchool of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
Rui XiaoSchool of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
Yuxiao DingSchool of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
Wenjie ShiSchool of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
Wei LiuSchool of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China. liuweiyxy@zzu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study represents the systematic examination of full lifecycle management for radiology artificial intelligence medical (AI) devices approved by the US Food and Drug Administration (FDA), with an in-depth analysis of post-market adverse events, recalls, and software update patterns. An analysis of 956 radiology AI medical devices approved by the FDA between September 1995 and September 2025 revealed that 429 (44.87%) of these devices had undergone software version updates. Adverse events related to software defects involved 15 products (34.88%); among these, 4 products (26.67%) underwent version updates, and for 3 products (20%), the companies initiated recalls following the occurrence of adverse events. There were a total of 124 reports (68.13%) of product recalls caused by software defects; for 38 of these reports (30.65%), corresponding to 8 products, the manufacturers corrected the defects by updating the software after implementing the recall. We make three contributions: (1) identifying that the vast majority of companies lack a closed-loop risk management system encompassing adverse events, recalls, and software updates, (2) analysing the frequency and characteristics of software updates for radiology equipment, and (3) exploring the critical role of full lifecycle management in the regulation of AI-based medical devices.

Identifiers

PMID42082591
PMCPMC13346426

What OpenQuestion holds

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Registered trials

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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.