Problems of translation of medical terms in the field of bone marrow donation

The article considers the problem of translation of medical terminology on the example of the sphere of bone marrow donation. The author considers medical text as a genre of scientific functional style and reveals the features of medical terms. The most common problems of translation of such terminology are ambiguous abbreviations, homonyms, synonyms, eponyms and Greek-Latin elements. The article analyses existing glossaries and dictionaries in this field in English and Russian language sources. Based on the results of the analysis, the importance of unifying the system of medical terms by expanding, enriching and systematizing the terminology system in bone marrow donation for the progress of medicine and improving the quality of translation is argued.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-04-01
Primary Topic
Reinforcement Learning in Robotics
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article
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article

Problems of translation of medical terms in the field of bone marrow donation

SHILAP Revista de lepidopterología
Reinforcement Learning in Robotics
article

Problems of translation of medical terms in the field of bone marrow donation

article en

Abstract

The article considers the problem of translation of medical terminology on the example of the sphere of bone marrow donation. The author considers medical text as a genre of scientific functional style and reveals the features of medical terms. The most common problems of translation of such terminology are ambiguous abbreviations, homonyms, synonyms, eponyms and Greek-Latin elements. The article analyses existing glossaries and dictionaries in this field in English and Russian language sources. Based on the results of the analysis, the importance of unifying the system of medical terms by expanding, enriching and systematizing the terminology system in bone marrow donation for the progress of medicine and improving the quality of translation is argued.

SHILAP Revista de lepidopterología
Ural Federal University (RU)
Quality Education
Openalex Percentile: Top 72%
Reinforcement Learning in Robotics
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