Feature Extraction Method from Electronic Health Records in Russia

The medical language is the basis of the electronic medical record (EHR), and up to 70 percent of the information in this record is written 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 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