title: Corpus-Based Problem Selection for EHR Note Summarization.
abstract: Physicians have access to patient notes in volumes far greater than what is practical to read within the context of a standard clinical scenario. As a preliminary step toward being able to provide a longitudinal summary of patient history, methods are examined for the automated extraction of relevant patient problems from existing clinical notes. We explore a grounded approach to identifying important patient problems from patient history. Methods build on existing NLP and text-summarization methodologies and leverage features observed in a relevant corpus.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY.
authors.forename: Tielman T
authors.initials: TT
authors.lastname: Van Vleck
authors.forename: Noémie
authors.initials: N
authors.lastname: Elhadad
mesh_terms: D057286:Electronic Health Records; D006801:Humans; D009323:Natural Language Processing; D010820:Physicians