Radiology research abstracts show a marked rise in LLM-assisted editing since the release of ChatGPT.
Key Details
- 1A study analyzed 32,335 English-language medical research abstracts (2020–2025), including 23,227 journal articles and 9,108 preprints across radiology, surgery, and internal medicine.
- 2For radiology journal articles, LLM-modified text increased from 0.5% pre-ChatGPT to 3% post-ChatGPT; for preprints, it rose from 1.4% to 7%.
- 3‘Alpha’ values measuring LLM influence grew from 1.1% (Q1 2023) to 6.5% (Q2 2025) in radiology articles and showed increases in Asia, Europe, and North America.
- 4Surgery and internal medicine also saw post-ChatGPT increases, though radiology preprints saw the sharpest rise.
- 5Authors caution that LLM use in writing isn't necessarily misconduct, as many journals have guidance on responsible AI use in scientific writing.
Why It Matters
Growing adoption of LLMs for drafting and editing radiology abstracts has implications for publication norms, author accountability, and transparency in radiological research. Understanding these trends can help journals and researchers align practices with evolving technology.
Source
AuntMinnie
Related News
•AuntMinnie
AI Model Uses Ultrasound to Assess Fetal Lung Maturity
Researchers demonstrated an AI model's strong accuracy in measuring fetal lung maturity from ultrasound images.
•AuntMinnie
AI Model Predicts Dosimetry for Lu-177 PSMA Therapy Using PET/CT
A machine learning PET/CT model shows promise for predicting radiation dose prior to Lu-177 PSMA therapy in prostate cancer patients.
•Radiology Business
AI Concerns Influence Medical Students' Interest in Radiology
AI is deterring a significant portion of medical students from choosing radiology as a career, though most remain optimistic about AI's benefits for the field.