Evidence map›Paper›PMID 41717587›Full record

ReviewEClinicalMedicine2026

Do world-wide policy initiatives for regulating health care related artificial intelligence safeguard the declaration of Helsinki?

Antonis A Armoundas, Joseph Loscalzo

Abstract readReview
In one paragraph

Review in EClinicalMedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Antonis A ArmoundasCardiovascular Research Center, Massachusetts General Hospital, United States.
Joseph LoscalzoBroad Institute, Massachusetts Institute of Technology, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital health technologies and artificial intelligence (AI), are transforming medical research, health care, and public health. The ever-increasing usage of algorithms in health care has challenged governments, regulatory agencies, health organizations, developers, and providers, and AI raises novel ethical challenges that extend beyond the jurisdiction of traditional borders and regulatory health-care processes and structures. While there is growing consensus in recognizing these ethical challenges, there is less agreement over the necessary AI guardrails. This Viewpoint offers a synthesis of representative AI-enabled health policy approaches across jurisdictions and advances practical recommendations for an adaptive, international AI policy and governance framework that will be responsible for monitoring and advancing its regulations in pace with the rapid growth of AI technologies. We use the Declaration of Helsinki as a normative reference point, to derive risk-proportionate safeguards for AI-enabled health across research and non-research settings.

Indexed as

Artificial intelligenceGlobalHuman rightsPolicyRegulation

Identifiers

PMID41717587
PMCPMC12914512

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.