Biomedical named entity recognition using deep neural networks with contextual information

摘要

With the increasing number of biomedical articles and resources, searching for and extracting valuable information has become challenging [ ]. Researchers consider multiple information sources and transform unstructured text data into refined knowledge to facilitate research productivity [ , ]. However, manual annotation and feature generation by biomedical experts are inefficient because they involve a complex process and require expensive and time-consuming labor [ ]. Therefore, efficient and accurate natural language processing (NLP) techniques are becoming increasingly important for use in computational data analysis, and advanced text mining techniques are necessary to automatically analyze the biomedical literature and extract useful information from texts [ – ].