A Report On The E-C Translation Of Artificial Intelligence In Healthcare (Excerpts)

The source text of this report is Chapter One and Chapter Seven from Artificial Intelligence in Healthcare by Adam Bohr and Kaveh Memarzadeh,which mainly introduces the present AI technology and AI in medical devices separately.The AI technologies and concepts involved have important value for future research.Therefore,the translation of the source text is valuable.The source text is a scientific text with various technical terms and long and complex sentences.Considering these features,the translator employs the relevance translation theory as the guiding theory,which requires the translator to first infer the original information with the cognitive environment and then choose the most suitable expression via the dual ostensiveinferential process to provide the best translation.In this report,research is conducted on the translation difficulties encountered from three levels,namely the lexical level,syntactical level,and textual level to explain how the translator employs multiple translation methods under the guidance of the relevance translation theory.At the lexical level,literal translation,free translation,and zero translation are adopted;at the syntactic level,linear translation,conversion,and division are employed;at the textual level,reiteration and amplification are used.The translator translates the source text with the above translation methods,trying to seek the optimal relevance in translation and hoping to provide some references for scientific text translation.