Authors: Shengyang Wu; Curtis P. Langlotz; Paras Lakhani; Lyle H. Ungar
Addresses: Department of Radiology, University of Michigan, Ann Arbor, MI 48104, USA ' Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA ' Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA ' Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA
Abstract: Health care providers often dictate their reports by filling in slots in templates. These slots can be filled with a variety of different procedures, measurements, or findings. Many radiologists currently create their own personalised templates, costing time and leading to inconsistencies across physicians. We present a sequence alignment method Radiology Content Alignment (RADICAL) that uses dynamic programming to efficiently extract templates that are common across sets of reports, and give examples of the extracted templates and the contents of their slots.
Keywords: medical informatics; sequence alignment; text mining; report generation; Feng-Doolittle; template extraction; common templates; radiology reports; dynamic programming; radiologists.
International Journal of Data Mining and Bioinformatics, 2012 Vol.6 No.6, pp.633 - 650
Received: 27 Jan 2010
Accepted: 10 Feb 2011
Published online: 11 Nov 2012 *