11/25/2023 0 Comments Deepl translator google![]() ![]() The match rates were calculated for the entire text and each of the four sections, namely, Introduction, Materials and Methods, Results, and Discussion. The number of sentences with matched meaning was counted, and the match rate of BTJ to OJ was calculated. In turn, the judges compared the OJ and BTJ for each sentence and determined whether the meanings were consistent. If the translation was not possible, it was marked as “untranslatable.” The re-translated Japanese text was termed as the back-translated manuscript in Japanese (BTJ). The translation was performed as literal translation, not free translation. An inappropriate word was translated as is. The method of the back translation was as follows. The automatically translated English text was back-translated into Japanese by translators. MT using DeepL Translator was performed for each section. The OJ was divided into four sections: Introduction, Materials and Methods, Results, and Discussion. The subject article (i.e., OJ) was translated from Japanese to English using the DeepL Translator in March 2021. For this article, an original draft written in Japanese (hereafter “OJ”) is available.īack translation and calculation of the match rateįigure Figure1 1 shows an overview of the study design. It describes a dose-volume analysis that is one of the major topics of interest in the field of radiation oncology. This article was published in a MEDLINE-indexed, English peer-reviewed scientific journal. Therefore, in this study, we investigated the accuracy of MT from Japanese to English for a medical article using the DeepL Translator.Īs the subject of this study, a medical article entitled “Dosimetric Comparison Between Carbon-Ion Radiotherapy and Photon Radiotherapy for Stage I Esophageal Cancer” was used. However, the reliability of DeepL Translator in translating medical articles has not yet been verified. ![]() DeepL Translator aims to provide accurate MT. It was launched in August 2017, and its Japanese translation service was launched in March 2020. ĭeepL Translator (DeepL GmbH, Cologne, Germany) is one of the MT applications employing neural network systems. Several studies have demonstrated that MT using neural networks shows higher translation accuracy in comparison with conventional SMT systems. Recently, MT systems employing different approaches, such as neural networks, have been developed. This approach employs a large amount of parallel text of the target language pair to train SMT models. ![]() Conventional MT uses the statistical machine translation (SMT) framework. MT reduces the time required for translation by 95% of that required for manual translation. The quality of MT has been improving, and it is widely used in various fields, such as business and translation services. Machine translation (MT) is a system that automatically translates one language into another. Writing medical articles in English is one of the obstacles faced by non-English-speaking researchers. The share of medical articles published from Japan is only 6% and is gradually declining. The translation for a medical article from Japanese to English was performed accurately by DeepL Translator.Īpproximately 50% of all international medical articles originate from non-English-speaking countries. Compound sentences and sentences with an unclear subject and predicate appeared to be significant predictors for mismatched translation. The match rate in the Results section was significantly higher than that in the other sections while the match rate in the Materials and Methods section was significantly lower than the rate in the other sections. The mean ± standard deviation of the match rate for the entire article was 94.0 ± 2.9%. In turn, three other researchers compared the back-translated Japanese sentences with the original Japanese manuscript and calculated the percentage of sentences that retained the intended meaning. The translated English article was then back-translated into Japanese by three researchers. The original Japanese manuscript was translated into English using DeepL Translator. The subject of this study was an English-language medical article translated from Japanese, which had already been published. In this study, we investigated the accuracy of machine translation from Japanese to English for a medical article using the DeepL Translator. ![]() The reliability of DeepL Translator (DeepL GmbH, Cologne, Germany) for the translation for medical articles has not been verified yet. ![]()
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