Semantic retrieval-augmented translation for radiology reports using small language models: Algorithm development and evaluation

Introduction

Accurate machine translation (MT) of clinical text is essential for multilingual patient care, cross-border data sharing, and research reproducibility, yet the use of commercial APIs for such tasks raises substantial privacy concerns. We present Semantic Retrieval-Augmented Translation (S-RAT), a lightweight, ontology-guided framework that integrates the Unified Medical Language System (UMLS) and SNOMED CT concept retrieval into large language model prompts to improve medical terminology fidelity without fine-tuning or external APIs.