Abstract:The MIMIC II database contains 1,237,686 clinical documents of various kinds. A common task for researchers working with this database is to run MetaMap, which uses the UMLS Metathesaurus, on those documents to identify specific semantic types of entities mentioned in them. However, this task is computationally expensive and time-consuming. Research in many groups could be accelerated if there were a community-accessible set of outputs from running MetaMap on this document collection, cached and available on t… Show more
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