![]() ![]() Most of the inaccuracy came from missing outcomes from the list, but a few arose from finding outcomes not captured in the reference extraction. Only 5 to 43 percent of translated articles yielded accurate lists of reported outcomes across languages. Extractors' accuracy in finding reported outcomes from lists of outcomes was generally poor, including from English articles (with only 63 percent accuracy). Translated Spanish articles generally yielded more accurate outcome descriptions and results data. The accuracy of descriptions of outcomes and results data (net difference, standard error, number of events or reported odds ratio, and P value of difference or odds ratio) varied widely by language, with descriptions of outcomes being commonly inaccurate from Chinese, German, and French articles, continuous results data (net difference and standard error) being inaccurate from French and Chinese articles, categorical results data (number of events or odds ratio) being inaccurate from German and Japanese articles, and P values being inaccurate in Japanese and Chinese articles. ![]() The odds ratios of accurate extractions compared with English followed similar patterns. For results reporting, there was consistently accurate extraction (mostly above about 85 percent) for the numbers of participants analyzed and whether mean or median data were reported. With slightly lower agreement, there were also generally good levels of agreement (mostly above 70 percent) for extraction of descriptions of the intervention (dose, frequency, route, duration) and the number of participants randomized. The discrepancy in the results from the translated Spanish articles are likely due to greater disagreement in data extraction (unrelated to translation issues) between individual pairs of extractors than between double data extracted and reconciled extractions and the translated extractions.Īcross languages, including English, we found good levels of agreement (mostly above 85 to 90 percent) for extraction of most study design questions (eligibility criteria funding source number of centers followup duration whether the study reported randomization, allocation concealment techniques, intention-to-treat and power calculations and who was blinded. 15 Our improved methods, including double data extraction of the original language articles together with adjustment for individual extractors' accuracy in extracting English articles provides better confidence in our conclusions. With the exception of Spanish, the findings of this analysis are generally consistent with, but more robust than, a similar analysis done as a pilot study. With the exception of Japanese (where we found that extraction was fairly accurate) difference across languages was similar to the findings of machine translation experts for general translation “that translations between European languages are usually good, while those involving Asian languages are often relatively poor.” 13 The least accurate data extractions resulted from translated Chinese articles. Specifically, extractions of Spanish articles were most accurate, followed by fairly accurate extractions from German, Japanese, and French articles. The accuracy of translation was heavily dependent on the original language of the article. But if you're trying to translate a classical novel written in Armenian, find a human translator.Our results showed that using Google Translate to translate medical articles in many cases may be feasible and not a resource-intensive process that leads to operationally workable English versions. You may never run into issues if you use it to translate directions, menu items, or phrases. However, since 2019, Google Translate has grown by adding more languages and features and improving its translation techniques. In a 2019 UCLA study based on medical instructions (where even the slightest ambiguity is unacceptable), they found a 94% accuracy rate for English to Spanish, compared to a 55% accuracy rate for English to Armenian. However, translation accuracy varies depending on the language. Instead, it relies on machine learning to decide the most accurate translation. Google Translate no longer performs a word-for-word match on text. ![]() While it can't grasp the subtle nuances of languages, it is more than adequate for everyday purposes. While many people might consider it a shallow translation tool at best, unable to translate the meaning in a sentence, its progress over the years cannot be denied. Google Translate is constantly improving. We show you how to use the Google Translate app to translate text, images, or audio and explain extra features like Live Translate. ![]()
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