Evidence map›Paper›PMID 41717567›Full record

ReviewFrontiers in psychiatry2026

Intelligent imaging triage systems for reducing waiting anxiety: a narrative review.

Qin Zhao, Haiyu Wang, Qingfeng Li

Abstract readReview
In one paragraph

Review in Frontiers in psychiatry, 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

3 authors.

Qin ZhaoDepartment of Medical Imaging, Dazhou Dachuan District People's Hospital, Dazhou Third People's Hospital, Dazhou, Sichuan, China.
Haiyu WangDepartment of Medical Imaging, Dazhou Dachuan District People's Hospital, Dazhou Third People's Hospital, Dazhou, Sichuan, China.
Qingfeng LiDepartment of Medical Imaging, Dazhou Dachuan District People's Hospital, Dazhou Third People's Hospital, Dazhou, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The delay in medical imaging exams can cause significant anxiety, impacting patient adherence, imaging quality, and overall experience. Intelligent imaging triage systems, driven by artificial intelligence in radiology, aim to improve examination processes and reduce patient anxiety. This review discusses the prevalence of patient anxiety during waiting periods, as well as the physiological and psychological mechanisms. In addition, the structure and functions of these systems, their current use in top domestic hospitals and international healthcare systems, and initial findings on anxiety reduction and enhanced patient satisfaction are analyzed. Some methods were proposed to address the challenges, such as limited evidence, sample representation, and durability assessment. Potential technological advancements, innovations in clinical services, and future interdisciplinary opportunities and policy implications were explored. Intelligent imaging triage systems have the potential to improve the medical workflow efficiency and provide emotional support within patient-centered care. This review concludes that while promising, the widespread adoption of these systems necessitates more robust evidence, interdisciplinary collaboration, and supportive policies.

Indexed as

artificial intelligence interventionintelligent imaging triage systemmedical imagingoptimization of medical workflowwaiting anxiety

Identifiers

PMID41717567
PMCPMC12913184

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.