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Evaluation of a Method to Identify and Categorize Section Headers in Clinical Documents
2009
JAMIA Journal of the American Medical Informatics Association
A b s t r a c t Objective: Clinical notes, typically written in natural language, often contain substructure that divides them into sections, such as "History of Present Illness" or "Family Medical History." The authors designed and evaluated an algorithm ("SecTag") to identify both labeled and unlabeled (implied) note section headers in "history and physical examination" documents ("H&P notes"). Design: The SecTag algorithm uses a combination of natural language processing techniques, word
doi:10.1197/jamia.m3037
pmid:19717800
pmcid:PMC3002123
fatcat:izyajgwonnaqpic5hpinvivkou