{"id":10268,"date":"2020-06-29T09:36:52","date_gmt":"2020-06-29T09:36:52","guid":{"rendered":"https:\/\/bgrssb.icgbio.ru\/2020\/2020\/06\/29\/named-entity-recognition-in-medical-texts-in-russian-using-deep-learning-models\/"},"modified":"2020-06-29T09:36:52","modified_gmt":"2020-06-29T09:36:52","slug":"named-entity-recognition-in-medical-texts-in-russian-using-deep-learning-models","status":"publish","type":"post","link":"https:\/\/bgrssb.icgbio.ru\/2020\/2020\/06\/29\/named-entity-recognition-in-medical-texts-in-russian-using-deep-learning-models\/","title":{"rendered":"Named entity recognition in medical texts in Russian using deep learning models"},"content":{"rendered":"<p>Igor Viktorovich Moskalev<sup>1<\/sup>, Luybov\\&#8217; Anatol\\&#8217;evna Khvorova<sup>2<\/sup><br \/><sup>1<\/sup>ASU, Barnaul, Russia, moskalev.igor.v@gmail.com<br \/><sup>2<\/sup>ASU, Barnaul, Russia, khvorovala@gmail.com<\/p>\n<p>The application of contextual and domain-specific pre-trained word embeddings for recognition of medical concepts in free-text clinical notes in Russian is considered. As it is known, a large amount of medical data is stored in electronic form, a significant part &#8211; in an unstructured form (medical history, extracts, description of the results of various tests). This data contains a large amount of useful information for the diagnosis of diseases. The results of the experiments showed the effectiveness of applying contextual language models which pre-trained on medical texts in the task biomedical named entity recognition.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Igor Viktorovich Moskalev1, Luybov\\&#8217; Anatol\\&#8217;evna Khvorova21ASU, Barnaul, Russia, moskalev.igor.v@gmail.com2ASU, Barnaul, Russia, khvorovala@gmail.com The application of contextual and domain-specific pre-trained word embeddings for recognition of medical concepts in free-text clinical notes in Russian is considered. As it is known, a large amount of medical data is stored in electronic form, a significant part &#8211; in an unstructured form (medical history, extracts, description of the results of various tests). This data contains a large amount of useful information for the diagnosis of diseases. The results of the experiments showed the effectiveness of applying contextual language models which pre-trained on medical texts in the task biomedical named entity recognition.<\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2168],"tags":[2072,1986,2070,2071,2073],"_links":{"self":[{"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/posts\/10268"}],"collection":[{"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/comments?post=10268"}],"version-history":[{"count":0,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/posts\/10268\/revisions"}],"wp:attachment":[{"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/media?parent=10268"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/categories?post=10268"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bgrssb.icgbio.ru\/2020\/wp-json\/wp\/v2\/tags?post=10268"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}