title: A best-fit model for concept vectors in biomedical research grants.
abstract: The Research, Condition, and Disease Categorization (RCDC) project was created to standardize budget reporting by research topic. Text mining techniques have been implemented to classify NIH grant applications into proper research and disease categories. A best-fit model is shown to achieve classification performance rivaling that of concept vectors produced by human experts.
authors.affiliation: Center for Information Technology, Office of Portfolio Analysis and Stategic Initiatives, National Institutes of Health, Bethesda, MD 20892, USA.
authors.forename: Calvin
authors.initials: C
authors.lastname: Johnson
authors.forename: William
authors.initials: W
authors.lastname: Lau
authors.forename: Archna
authors.initials: A
authors.lastname: Bhandari
authors.forename: Timothy
authors.initials: T
authors.lastname: Hays
mesh_terms: D001185:Artificial Intelligence; D035843:Biomedical Research / Q000145:classification*; D005380:Financing, Government / Q000145:classification / Q000191:economics; D009316:National Institutes of Health (U.S.); D009323:Natural Language Processing; D012109:Research Support as Topic / Q000145:classification* / Q000191:economics*; D014481:United States