Evidence map›Paper›PMID 42849887›Full record

ReviewKorean journal of radiology2026

Is Vibe Coding a 'Fire of Prometheus' for Non-Developer Clinicians, Especially Clinical Radiologists?

Sung Il Hwang, Hunjong Lim, Kyong Joon Lee, Hak Jong Lee, Hyungwoo Ahn, Yoojin Nam, Masahiro Jinzaki

Abstract readReview
In one paragraph

Review in Korean journal of radiology, 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

7 authors.

Sung Il HwangDepartment of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID https://orcid.org/0000-0001-7516-5369
Hunjong LimDepartment of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea. limhunjong@naver.com.ORCID https://orcid.org/0000-0002-8512-6977
Kyong Joon LeeDepartment of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID https://orcid.org/0000-0002-0658-433X
Hak Jong LeeDepartment of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea.ORCID https://orcid.org/0000-0003-0858-7873
Hyungwoo AhnDepartment of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.ORCID https://orcid.org/0000-0003-3266-6176
Yoojin NamDepartment of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-8565-1360
Masahiro JinzakiDepartment of Radiology, Keio University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0002-8241-6565

Funding

Seoul National University Bundang Hospital 18-2025-0015
6 · The paper itself

Abstract

Vibe coding is a workflow in which users describe the desired software behavior in natural language, following which large language models (LLMs) generate the code. It is increasingly being used by non-developer clinicians without any formal programming training to create tools that support the clinical workflow. This development is both timely and consequential for radiology, one of the specialties both most exposed to artificial intelligence (AI)-driven automation and best positioned to adopt it owing to its longstanding engagement with imaging AI, digital infrastructure, and information system workflows. Therefore, radiologists may become not merely passive AI users, but also clinical workflow orchestrators. This opportunity is illustrated by a structured prostate magnetic resonance imaging reporting tool, vibe-coded by a non-developer radiologist in approximately four hours, with an institution-based voluntary, radiologist-led coding community. This investigation highlighted four cautions: erosion of domain expertise, risks to security and patient data, absence of peer feedback, and uncoordinated proliferation of tools. A minimum safeguard set for clinician-built tools was proposed. As previously framed, LLMs represent a "fire of Prometheus" for non-native English-speaking researchers. Similarly, vibe coding may warm and burn radiologists equally, with its impact determined less by technology than by how responsibly the specialty adopts it.

Indexed as

Artificial IntelligenceClinical CodingMagnetic Resonance ImagingRadiologistsRadiologyRadiology Information SystemsWorkflowHumansLarge Language ModelsMaleArtificial intelligenceClinical medicineGovernanceLarge language modelOrchestrationProgrammingRadiologyVibe codingWorkflow

Identifiers

PMID42849887
PMCPMC13655311

What OpenQuestion holds

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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.