NER-DD: A Named Entity Recognition Tool for Tagging Drugs in Disease-related Documents

Abstract

The amount of biomedical documents is increasing daily. Therefore, several tools intent to identify automatically important information in those documents such as genes, disease, drugs among others. Depending on the tool selected, the combination of the type of input documents, tagging model, and output information presents some disadvantages. This work attempt to gather three functionalities, the capability of use not only PubMed abstracts but also PDF or TXT files, a neural-based named entity recognition approach, and display co-occurrence tables. Therefore, we present NER-DD a tool for tagging drugs in disease-related documents to determine possible associations between them.