Extracting templates from radiology reports using sequence alignment
Shengyang Wu, Curtis P. Langlotz, Paras C. Lakhani, Lyle Ungar · International Journal of Data Mining and Bioinformatics · 2012
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.