It is now almost 15 years since the publication of the first paper on text mining in the
genomics domain, and decades since the first paper on text mining in the medical domain …

Taxonomists are arguably the most active annotators of the natural world, collecting and
publishing millions of phenotype data annually through descriptions of new taxa. By …

The Handbook of Natural Language Processing, Second Edition presents practical tools
and techniques for implementing natural language processing in computer systems. Along …

Text mining is defined by Hearst (1999) as the automatic discovery of new, previously
unknown, information from unstructured textual data. This is often seen as comprising of …

Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …

New approaches to biomedical text mining crucially depend on the existence of
comprehensive annotated corpora. Such corpora, commonly called gold standards, are …

Today's biomedical research has become heavily dependent on access to the biological
knowledge encoded in expert curated biological databases. As the volume of biological …

The biomedical literature can be seen as a large integrated, but unstructured data
repository. Extracting facts from literature and making them accessible is approached from …

Although text mining shows considerable promise as a tool for supporting the curation of
biomedical text, there is little concrete evidence as to its effectiveness. We report on three …

Manual curation of data from the biomedical literature is a rate-limiting factor for many expert
curated databases. Despite the continuing advances in biomedical text mining and the …