{"id":43,"date":"2022-04-01T09:17:47","date_gmt":"2022-04-01T09:17:47","guid":{"rendered":"https:\/\/temu.bsc.es\/clinspen\/?page_id=43"},"modified":"2023-03-09T12:14:40","modified_gmt":"2023-03-09T12:14:40","slug":"clinspen","status":"publish","type":"page","link":"https:\/\/temu.bsc.es\/clinspen\/","title":{"rendered":"ClinSpEn"},"content":{"rendered":"\n

ClinSpEn<\/strong><\/h1>\n\n\n\n

<\/p>\n\n\n\n

This website contains the data for the ClinSpEn<\/strong> shared task, focused on clinical EN-ES machine translation<\/strong> and part of the biomedical task of<\/strong> WMT 2022<\/a><\/strong>.<\/p>\n\n\n\n

The Gold Standard test sets for every dataset have been released. They are available on Zenodo<\/a>.<\/p>\n\n\n\n

The BioWMT 2022 overview paper is now available! You can find it here<\/a>. If you use any of the ClinSpEn data, please remember to cite it.<\/p>\n\n\n\n

Motivation<\/h3>\n\n\n\n

Machine translation applied to the clinical domain is a specially challenging task due to the complexity of medical language and the heavy use of health-related technical terms and medical expressions. Therefore there is a large community of specialized medical translators, able to deal with medical narratives, terminologies or the use of ambiguous abbreviations and acronyms. <\/p>\n\n\n\n

Taking into account the relevance, impact and diversity of health-related content, as well as the rapidly growing number of publications, EHRs, clinical trials,  informed consent documents and medical terminologies there is a pressing need to be able to generate more robust medical machine translation resources together with independent quality evaluation scenarios.  <\/p>\n\n\n\n

Recent advances in machine translation technologies together with the use of other NLP components are showing promising results, thus domain adaptation of MT approaches can have a significant impact in unlocking key information from medical content.<\/p>\n\n\n\n

Therefore, the ClinSpEn data represents three different types of data very relevant to the biomedical domain: clinical cases, clinical terminology and ontology concepts.<\/p>\n\n\n\n

Sub-tracks<\/h3>\n\n\n\n

All in all, ClinSpEn is comprised of three different sub-tracks:<\/p>\n\n\n\n