| Literature DB >> 21347092 |
Tielman T Van Vleck1, Noémie Elhadad.
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.Entities:
Mesh:
Year: 2010 PMID: 21347092 PMCID: PMC3041431
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076