Abstract
Physicians often use information from previous clinical cases in their decision-making process. However, the large amount of patient records available in hospitals makes an exhaustive search unfeasible. We propose a method for the retrieval of similar clinical cases, based on mapping the text onto UMLS concepts and representing the patient records as semantic graphs. The method also deals with the problems of negation detection and concept identification in clinical free text. To evaluate the approach, an evaluation collection has been developed. The results show that our method correlates well with the expert judgments and outperforms remarkably the traditional term-vector space model.
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References
Gorman, P., Helfand, M.: Information seeking in primary care: how physicians choose which clinical question to pursuit and which to leave unanswered. Medical Decision Making 15, 113–119 (1995)
Ely, J., Osheroff, J., Ebell, M., Chambliss, M., Vinson, D., Stevermer, J., Pifer, E.: Obstacles to answering doctors’ questions about patient care with evidence: qualitative study. British Medical Journal 324, 710–713 (2002)
Hersh, W., Hickam, D.: Information retrieval in medicine: The Saphire experience. Journal of the American Society for Information Science 46, 743–747 (1995)
Lacoste, C., Lim, J., Chevallet, J., Le, D.: Medical-image retrieval based on knowledge-assisted text and image indexing. IEEE Transactions on Circuits and Systems for Video Technology 17, 889–890 (2007)
Navarro, S., Llopis, F., Muñoz, R.: Different Multimodal Approaches using IR-n in ImageCLEFphoto 2008. In: On-line Working Notes CLEF (2008)
Kwiatkowska, M., Atkins, S.: Case representation and retrieval in the diagnosis and treatment of obstructive sleep apnea: A semiofuzzy approach. In: Proceedings of the 7th ECCBR (2004)
Gindl, S., Kaiser, K., Miksch, S.: Syntactical negation detection in clinical practice guidelines (2008)
Mutalik, A., Deshpande, A., Nadkarni, P.: Use of general-purpose negation detection to augment concept indexing of medical documents. A quantitative study using the UMLS. JAIMA 8, 598–609 (2001)
Morante, R., Liekens, A., Daelemans, W.: Learning the scope of negation in biomedical texts. In: Proceedings of the EMNLP Conference, pp. 715–724 (2008)
Nadkarni, P.: Information retrieval in medicine: overview and applications. Journal of Postgraduate Medicine 46, 122–166 (2000)
Nelson, S., Powell, T., Humphreys, B.: The Unified Medical Language System (UMLS) Project. In: Kent, A., Hall, C.M. (eds.) Encyclopedia of Library and Information Science, Marcel Dekker, Inc., New York (2002)
Aronson, A.: Effective mapping of biomedical text to the umls metathesaurus: the metamap program. In: Proceedings of the AMIA Annual Symposium, pp. 17–21 (2001)
Pratt, W., Yetisgen-Yildiz, M.: A study of biomedical concept identification: Metamap vs. people. In: Proceedings of the AMIA Annual Symposium, pp. 529–533 (2003)
Yoo, I., Hu, X., Song, I.Y.: A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method. BMC Bioinformatics 8(9) (2007)
Cohen, J.: A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20, 37–46 (1960)
Salton, G.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1983)
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Plaza, L., Díaz, A. (2010). Retrieval of Similar Electronic Health Records Using UMLS Concept Graphs. In: Hopfe, C.J., Rezgui, Y., Métais, E., Preece, A., Li, H. (eds) Natural Language Processing and Information Systems. NLDB 2010. Lecture Notes in Computer Science, vol 6177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13881-2_31
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DOI: https://doi.org/10.1007/978-3-642-13881-2_31
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