Bridging Language Barriers in Radiology: The Role of Large Language Models in Supporting International Trainees

Introduction

Globalization in medicine has expanded cross-border training, presenting challenges for non-native speakers adapting to local language and medical terminology. Radiological reporting requires not only clinical expertise but also proficiency in region-specific standards. For international trainees, this linguistic adaptation can significantly impact report quality and learning outcomes. Innovative tools like large language models (LLMs), such as ChatGPT, offer solutions by providing translation assistance and structured outputs [1] [2] [3]; these hold potential to transform medical education and streamline reporting processes.

This editorial shares insights from the first author's experience as a non-German speaking radiologist at a German academic institution, focusing on the potential of LLMs like ChatGPT to facilitate radiological reporting and enhance the learning experience for international trainees, particularly non-native speakers.

Publication History

Received: 14 December 2024

Accepted after revision: 09 March 2025

Article published online:
10 April 2025

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