Evidence map›Paper›PMID 40747091›Full record

ReviewFrontiers in medicine2025

A decade of review in global regulation and research of artificial intelligence medical devices (2015-2025).

Siwen Zhang, Yujun Li, Wenxi Liu, Qi Chu, Shasha Wang, Jinyu Li, Yuwen Chen

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review 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 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Siwen ZhangSchool of Medical Device, Shenyang Pharmaceutical University, Shenyang, China.
Yujun LiSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang, China.
Wenxi LiuSchool of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang, China.
Qi ChuDepartment of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China.
Shasha WangDepartment of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China.
Jinyu LiSchool of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, China.
Yuwen ChenSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) and medical devices are increasingly integrated, reshaping global diagnostic paradigms. However, the adaptive learning and opaque nature of AI technologies pose significant challenges to traditional regulatory frameworks. In response, regulatory bodies worldwide, including the U.S., EU, China, Japan, and South Korea, have initiated various policies to address the unique risks posed by AI medical devices (AIMD). These efforts aim to balance innovation with patient safety, yet gaps remain in harmonizing standards across regions and ensuring comprehensive oversight. This study provides a comprehensive analysis of the regulatory policies for AIMD from 2015 to 2025 across key global regions. We examine the evolution of these policies, the academic research progress, the limitations of existing regulations, and emerging trends. By reviewing relevant legislation and literature, this paper offers valuable insights for researchers, manufacturers, and regulators to foster the development of robust regulatory frameworks for AIMD.

Indexed as

artificial intelligence medical deviceinnovation and safetyinternational harmonizationregulatory policytotal product life cycle (TPLC) management

Identifiers

PMID40747091
PMCPMC12310608

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.