Evidence map›Paper›PMID 42200797›Full record

ArticleRadiology. Artificial intelligence2026

Alignment of Policy, Practice, and Patient Safety for Trustworthy AI in Radiology.

Florence X Doo, Melissa A Davis, Jason Poff, Yvonne W Lui, Kevin Haines, Alexander J Towbin

Abstract read
In one paragraph

Article in Radiology. Artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Florence X DooUniversity of Maryland-Institute for Health Computing (UM-IHC), North Bethesda, Md.ORCID 0000-0001-6519-5222
Melissa A DavisDepartment of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Conn.ORCID 0000-0003-4952-4916
Jason PoffRadiology Partners, Nashville, Tenn.ORCID 0009-0006-6692-1007
Yvonne W LuiDepartment of Radiology, New York Langone Health/Grossman School of Medicine, New York, NY.ORCID 0000-0002-9984-9164
Kevin HainesDepartment of Radiology, University of Connecticut Health Center, Farmington, Conn.ORCID 0009-0002-2051-3789
Alexander J TowbinDepartment of Radiology, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, Ohio.ORCID 0000-0003-1729-5071

Funding

Understanding and addressing risks of low socioeconomic status and diabetes for heart failureP50MD017348 · NIMHD · JOHNS HOPKINS UNIVERSITY · PI IBE, CHIDINMA ADANNA · 2021 to 2025
$24.2M
Mild Traumatic Brain Injury Unveiled Using Diffusion MRI as an in vivo MicroscopeR01NS119767 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Sohae Chung, Yvonne W Lui · 2021 to 2026
$3.2M
CTSA K12 Program at Johns HopkinsK12TR004925 · NCATS · JOHNS HOPKINS UNIVERSITY · PI KHALIL G GHANEM · 2025 to 2026
$3.2M
Optimized Sodium MR Imaging at Clinical Field Strength to Study in vivo Sodium Signal in Mild Traumatic Brain InjuryR01NS131458 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Yvonne W Lui, Yongxian Qian · 2023 to 2026
$2.6M
NCATS NIH HHS K12 TR004925NIMHD NIH HHS P50 MD017348NINDS NIH HHS R01 NS119767NINDS NIH HHS R01 NS131458
6 · The paper itself

Abstract

Artificial intelligence (AI) has progressed from technical research to routine clinical use, reaching an inflection point where technological capabilities may exceed current regulatory and oversight frameworks. These systems are becoming more complex, progressing from narrow, task-specific algorithms to foundation models and early agentic prototypes. This progression has redistributed risk, responsibility, and clinical judgment, requiring radiologists and health care leaders to understand how policy choices affect patient safety and clinical innovation advancement. This special report provides a roadmap for aligning policy with clinical practice through a practical, lifecycle-based framework centered on patient safety.

Indexed as

Artificial IntelligenceHealth PolicyPatient SafetyRadiologyHumansUnited StatesUnited States Food and Drug AdministrationArtificial IntelligenceFood and Drug AdministrationHealth PolicyImplementation ScienceLarge Language ModelsMachine LearningPatient SafetyRegulatory ScienceTranslational Bialignment

Identifiers

PMID42200797
PMCPMC13349408

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.