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Peer-reviewedCC BY-NCKorean journal of radiology

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

  • Sung Il Hwang1
  • Hunjong Lim2
  • Kyong Joon Lee1
  • Hak Jong Lee3
  • Hyungwoo Ahn1
  • Yoojin Nam4,5
  • Masahiro Jinzaki6
6 affiliations
  1. 1Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  2. 2Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea. [email protected].
  3. 3Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea.
  4. 4Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
  5. 5Aperivue, Incheon, Republic of Korea.
  6. 6Department of Radiology, Keio University School of Medicine, Tokyo, Japan.
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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.

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Cite

BibTeXRIS
BibTeX
@article{hwang2026vibe,
  title = {{Is Vibe Coding a 'Fire of Prometheus' for Non-Developer Clinicians, Especially Clinical Radiologists?}},
  author = {Sung Il Hwang and Hunjong Lim and Kyong Joon Lee and Hak Jong Lee and Hyungwoo Ahn and Yoojin Nam and Masahiro Jinzaki},
  journal = {Korean journal of radiology},
  year = {2026},
  month = oct,
  doi = {10.3348/kjr.2026.0914},
  url = {https://europepmc.org/article/MED/42849887},
  note = {CC BY-NC},
}
RIS
TY  - JOUR
TI  - Is Vibe Coding a 'Fire of Prometheus' for Non-Developer Clinicians, Especially Clinical Radiologists?
AU  - Sung Il Hwang
AU  - Hunjong Lim
AU  - Kyong Joon Lee
AU  - Hak Jong Lee
AU  - Hyungwoo Ahn
AU  - Yoojin Nam
AU  - Masahiro Jinzaki
PY  - 2026
DA  - 2026/10/01
JO  - Korean journal of radiology
DO  - 10.3348/kjr.2026.0914
UR  - https://europepmc.org/article/MED/42849887
AB  - 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.
SN  - 1229-6929
SN  - 2005-8330
ER  -