Exploring Turkish equivalents of terms for musculoskeletal radiology: insights for a standardized terminology

Year 2025, Volume: 8 Issue: 2, 275 - 285, 21.03.2025

Zeynep Başer

https://doi.org/10.32322/jhsm.1612372

Abstract

Aims: This study aimed to provide an analysis of Turkish equivalents of English terms for musculoskeletal radiology.
Methods: The present study focuses on a global endorsement of English terms in musculoskeletal radiology, and explores how their Turkish equivalents are used in reference books (Turkish translation of the books, Diagnostic Imaging: Musculoskeletal: Trauma and Diagnostic Imaging: Musculoskeletal: Non-Traumatic Disease). Furthermore, the study attempts to provide a picture of how AI-based tools (i.e. neural machine translation tools such as DeepL, Google Translate and an AI Chatbot, ChatGPT) vary in the translation of these terms.
Results: The study found that the most common translation strategies for musculoskeletal radiology terms were borrowing and literal translation, with several combined strategies used for complex terms. AI-based tools like DeepL, Google Translate, and ChatGPT showed a high similarity to human translations, but differences were observed in word choice, strategy use, and orthographic variations. These differences, though minor, highlight the challenges of achieving consistency and accuracy in AI-generated medical translations.
Conclusion: The present study provides a list of Turkish equivalents for musculoskeletal terminology in English, and presents an analysis of translations by radiology specialists and AI-based tools. Careful evaluation of AI translations is essential to ensure accuracy and consistency in the translation of medical terminology, particularly in subspecialities such as musculoskeletal radiology.

Keywords

Radiology, musculoskeletal radiology, AI-based translation tools, terminology

Ethical Statement

I/we declare that the study with the above information is among the studies that do not require ethics committee permission.

Kas iskelet radyolojisi terimlerinin Türkçe karşılıklarının araştırılması: standartlaştırılmış bir terminoloji için öngörüler

Abstract

Amaç: Bu çalışmanın amacı kas-iskelet sistemi radyolojisinde kullanılan İngilizce terimlerin Türkçe karşılıklarının analizini yapmaktır.

Yöntemler: Bu çalışma, kas-iskelet radyolojisi alanındaki İngilizce terimlerin genel bir onayına odaklanmakta ve bunların Türkçe karşılıklarının referans kitaplarda nasıl kullanıldığını araştırmaktadır (Diagnostic Imaging: Musculoskeletal: Travma ve Tanısal Görüntüleme: Musculoskeletal: Travma Dışı Hastalıklar). Çalışma ayrıca, yapay zeka tabanlı araçların (yani DeepL, Google Translate gibi nöral makine çevirisi araçları ve bir yapay zeka sohbet robotu olan ChatGPT) bu terimlerin çevirisinde nasıl farklılık gösterdiğine dair bir resim sunmaya çalışmaktadır.

Bulgular: Çalışma, kas-iskelet radyolojisi terimleri için en yaygın çeviri stratejilerinin ödünç alma ve birebir çeviri olduğunu ve karmaşık terimler için birkaç birleşik stratejinin kullanıldığını ortaya koymuştur. DeepL, Google Translate ve ChatGPT gibi yapay zeka tabanlı araçlar insan çevirilerine yüksek oranda benzerlik gösterse de kelime seçimi, strateji kullanımı ve imla varyasyonlarında farklılıklar gözlemlenmiştir. Bu farklılıklar, küçük olsa da, YZ tarafından üretilen tıbbi çevirilerde tutarlılık ve doğruluk elde etmenin zorluklarını vurgulamaktadır.

Sonuç: Bu çalışma, İngilizce kas-iskelet sistemi terminolojisinin Türkçe karşılıklarının bir listesini sunmakta ve radyoloji uzmanları ve YZ tabanlı araçlar tarafından yapılan çevirilerin bir analizini sunmaktadır. YZ çevirilerinin dikkatli bir şekilde değerlendirilmesi, özellikle kas-iskelet radyolojisi gibi alt uzmanlık alanlarında tıbbi terminolojinin çevirisinde doğruluk ve tutarlılığı sağlamak için gereklidir.

Keywords

radyoloji, kas iskelet radyolojisi, yapay zeka tabanlı çeviri araçları, terimbilimi

Ethical Statement

Yukarıda bilgileri yer alan çalışmanın, etik kurul izni gerektirmeyen çalışmalar arasında yer aldığını beyan ederim/ederiz.

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