Biomedical Named Entity Recognition Under Low-Resource Situation

Biomedical named entity recognition is Key technology for automatic processing of health medical information. However, it is labor-expensive for get enough labeled data and always facing low-resource situation. We propose a method for biomedical named entity recognition that under low-resource situation. Our work is based on the 8th China Health Information Processing Conference task-1 and ranked third among all the teams. In the final results of the test set, the precision is $$38.07\%$$ , the recall is $$51.04\%$$ and the F1-score is 43.61.