Named Entity Recognition (NER) is a key component in NLP systems for question
answering, information retrieval, relation extraction, etc. NER systems have been studied …

Abstract PubTator Central (https://www. ncbi. nlm. nih. gov/research/pubtator/) is a web
service for viewing and retrieving bioconcept annotations in full text biomedical articles …

Background Finding biomedical named entities is one of the most essential tasks in
biomedical text mining. Recently, deep learning-based approaches have been applied to …

We present the approach of the Turku NLP group to the PharmaCoNER task on Spanish
biomedical named entity recognition. We apply a CRF-based baseline approach and …

The amount of biomedical literature is vast and growing quickly, and accurate text mining
techniques could help researchers to efficiently extract useful information from the literature …

One of the biomedical entity types of relevance for medicine or biosciences are chemical
compounds and drugs. The correct detection these entities is critical for other text mining …

In commercial research and development projects, public disclosure of new chemical
compounds often takes place in patents. Only a small proportion of these compounds are …

Abstract The Precision Medicine Initiative is a multicenter effort aiming at formulating
personalized treatments leveraging on individual patient data (clinical, genome sequence …

Background Chemical and biomedical named entity recognition (NER) is an essential
preprocessing task in natural language processing. The identification and extraction of …

Biomedical literature has become a rich source of information for various applications.
Automatic text mining methods can make the processing of extracting information from a …