Related Experiment Video
Updated: Feb 2, 2026

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible
Published on: January 28, 2020
Effect of ChatGPT-Assisted Reflective Reasoning on Guideline-Concordant Procedural Decision-Making Among Early-Career
Yunus Yasar1, Mustafa Demir1, Ali Canturk2
1University of Health Sciences, Umraniye Training and Research Hospital, Department of Radiology, Istanbul, Turkey (Y.Y, M.D., S.O., A.H.T., Y.A.).
Rationale And Objectives:
This study aims to evaluate the effect of ChatGPT-assisted reflective reasoning on guideline-concordant procedural decision-making among early-career interventional radiologists using standardized clinical scenarios based on the American College of Radiology Appropriateness Criteria.
Materials And Methods:
This prospective simulation-based study included 128 scenarios across common interventional radiology indications. Two expert interventional radiologists served as the reference standard. Three early-career radiologists completed all scenarios twice: first independently (pre-ChatGPT) and, after a two-month washout period, with access to ChatGPT-generated reasoning before recording final decisions (post-ChatGPT). Guideline concordance was assessed using a three-tier scoring system (appropriate = 2, may be appropriate = 1, inappropriate = 0) and a binary score reflecting avoidance of inappropriate decisions. Predifferences and postdifferences were analyzed with Wilcoxon signed-rank and McNemar tests. Agreement with experts was measured using Cohen's kappa.
Results:
ChatGPT-assisted reflective reasoning significantly improved guideline-concordant decision-making. The mean detailed compliance score increased from 1.697 to 1.900, and minimal compliance enhanced from 90.89% to 98.70%. A total of 30 scenario-level corrections shifted from inappropriate to guideline-concordant selections (McNemar χ² = 27.03; p < 0.0001). Detailed compliance improved significantly for all radiologists (p < 0.01). Weighted Cohen's kappa increased from 0.08-0.13 to 0.21-0.30, indicating better agreement with expert consensus. Performance variability decreased, narrowing the gap between early-career radiologists and experts.
Conclusion:
ChatGPT-assisted reflective reasoning enhanced guideline alignment and reduced inappropriate procedural selections among early-career interventional radiologists. These findings support the role of large language models as cognitive support tools during early clinical practice and warrant prospective evaluation in real-world settings.
More Related Videos
Related Concept Videos
Reason and Intuition
Reasoning
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
Pre-Procedural Guidelines for Assessing Blood Pressure
Kendall's Coefficient of Concordance
Deductive Reasoning
For example, a researcher can deduce specific predictions...
Inductive Reasoning
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...

