Extraction of Recommendation Features in Radiology with Natural Language Processing: Exploratory Study

OBJECTIVE. The purposes of this study were to validate a natural language processing program for extraction of recommendation features, such as recommended time frames and imaging technique, from electronic radiology reports and to assess patterns of recommendation features in a large database of radiology reports.MATERIALS AND METHODS. This study was performed on a radiology reports database covering the years 1995–2004. From this database, 120 reports with and without recommendations were selected and randomized. Two radiologists independently classified these reports according to presence of recommendations, time frame, and imaging technique suggested for follow-up or repeated examinations. The natural language processing program then was used to classify the reports according to the same criteria used by the radiologists. The accuracy of classification of recommendation features was determined. The program then was used to determine the patterns of recommendation features for different patients and im...