Gavrilov D., Gusev A., Korsakov I., Novitsky R., Serova L.
FRUCT ASSOCIATION, April 2020
Abstract^ The medical language is the basis of the electronic medical records (EHR), and up to 70 percent of the information in these records were writing in natural language, in the free text part. The last few years have seen a surge in the number of accurate, fast, publicly available name entity recognition (NER) parsers. At the same time, the use of NER parsing in natural language processing (NLP) applications has increased. It can be difficult for a non-expert to select a good “off-the-shelf” parser. We present a method of using statistical NER parsers on a medical corpus of Russian. We developed a new tool that gives a convenient way to extract NER from unstructured medical documents.
Download pdf|1,1 МБ
Subscribe to our newsletter
Are you interested in digital healthcare and artificial intelligence for medicine? Join our mailing list!