Chemical Entity Recognition for MEDLINE Indexing.
Savery M, Rogers W, Pillai M, Mork JG, Demner-Fushman D
AMIA 2020 Virtual Informatics Summit, 2020.
Abstract:
Chemical entity recognition is essential for indexing scientific literature in the MEDLINE database at the National Library of Medicine. However, the tool currently used to suggest terms for indexing, the Medical Text Indexer, was not originally conceived as a chemical recognition tool. It has instead been adapted to the task via its use of MetaMap and the addition of in-house patterns and rules. In order to develop a tool more suitable for chemical recognition, we have created a collection of 200 MEDLINE titles and abstracts annotated with genes, proteins, inorganic and organic chemicals, as well as other biological molecules. We use this collection to evaluate eleven chemical entity recognition systems, where we seek to identify a tool that effectively recognizes chemical entities for indexing and also performs well on chemical recognition beyond the indexing task. We observe the highest performance with a SciBERT ensemble.
Savery M, Rogers W, Pillai M, Mork JG, Demner-Fushman D. Chemical Entity Recognition for MEDLINE Indexing.
AMIA 2020 Virtual Informatics Summit, 2020.