Broad-coverage biomedical relation extraction with SemRep

摘要

A massive amount of biomedical knowledge is buried in free text, including scientific publications and clinical narratives. Natural language processing (NLP) techniques are increasingly used to extract from free text biomedical concepts, such as disorders, medications, tests, and genes/proteins, as well as relationships between them, including disease treatments, protein/drug interactions, and adverse drug events. Such techniques transform unstructured text into computable semantic representations, which can in turn support biomedical knowledge management and discovery applications, allowing clinicians and bench scientists to more efficiently access information and generate new knowledge.