Abstract
Radiological measurements (e.g., ‘3.2 x 1.4 cm’) are the predominant type of quantitative data in free-text radiology reports. We report on the development and evaluation of a classifier that labels measurement descriptors with the exam they refer to: current and/or prior exam. Our classifier aggregates regular expressions as binary features in a maximum entropy model. It has average F-measure 0.942 on 2,000 annotated instances; the rule-based baseline algorithm has F-measure 0.795. Potential applications and routes for future are discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Xu, H., Stenner, S.P., Doan, S., Johnson, K.B., Waitman, L.R., Denny, J.C.: MedEx: A medication information extraction system for clinical narratives. J. Am. Med. Inform. Assoc. 17(1), 19–24 (1996)
Cook, T.S., Zimmerman, S., Maidment, A.D., Kim, W., Boonn, W.W.: Automated extraction of radiation dose information for CT examinations. J. Am. Coll. Radiol. 7(11), 871–877 (2010)
Aronson, A.R., Lang, F.M.: An overview of MetaMap: Historical perspective and recent advances. J. Am. Med. Inform. Assoc. 17(3), 229–236 (2010)
Dreyer, K.J., Kalra, M.K., Maher, M.M., Hurier, A.M., Asfaw, B.A., Schultz, T., Halpern, E.F., Thrall, J.H.: Application of recently developed computer algorithm for automatic classification of unstructured radiology reports: Validation study. Radiology 234(2), 323–329 (2005)
Friedman, C., Alderson, P.O., Austin, J.H.M., Cimino, J.J., Johnson, S.B.: A general natural-language text processor for clinical radiology. J. Am. Med. Inform. Assoc. 1, 161–174 (1994)
Nigam, K.: Using maximum entropy for text classification. In: IJCAI 1999 Workshop on Machine Learning for Information Filtering, pp. 61–67 (1999)
Chapman, W.W., Bridewell, W., Hanbury, P., Cooper, G.F., Buchanan, B.G.: A simple algorithm for identifying negated findings and diseases in discharge summaries. J. Biomed. Inform. 34(5), 301–310 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sevenster, M. (2013). Classifying Measurements in Dictated, Free-Text Radiology Reports. In: Peek, N., Marín Morales, R., Peleg, M. (eds) Artificial Intelligence in Medicine. AIME 2013. Lecture Notes in Computer Science(), vol 7885. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38326-7_43
Download citation
DOI: https://doi.org/10.1007/978-3-642-38326-7_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38325-0
Online ISBN: 978-3-642-38326-7
eBook Packages: Computer ScienceComputer Science (R0)