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A Textual Recommender System for Clinical Data

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Book cover Case-Based Reasoning Research and Development (ICCBR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11156))

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Abstract

When faced with an exceptional clinical case, doctors like to review information about similar patients to guide their decision-making. Retrieving relevant cases, however, is a hard and time-consuming task: Hospital databases of free-text physician letters provide a rich resource of information but are usually only searchable with string-matching methods. Here, we present a recommender system that automatically finds physician letters similar to a specified reference letter using an information retrieval procedure. We use a small-scale, prototypical dataset to compare the system’s recommendations with physicians’ similarity judgments of letter pairs in a psychological experiment. The results show that the recommender system captures expert intuitions about letter similarity well and is usable for practical applications.

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Notes

  1. 1.

    e.g., Journal of Medical Cases: http://www.journalmc.org/index.php/JMC/index, British Medical Journal Case Reports: http://casereports.bmj.com/site/about/index.xhtml, American Journal of Medical Case Reports: http://www.sciepub.com/journal/AJMCR.

References

  1. Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Commun. 7(1), 39–59 (1994). https://doi.org/10.3233/AIC-1994-7104

    Article  Google Scholar 

  2. Begum, S., Ahmed, M.U., Funk, P., Xiong, N., Folke, M.: Case-based reasoning systems in the health sciences: a survey of recent trends and developments. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 41(4), 421–434 (2011). https://doi.org/10.1109/TSMCC.2010.2071862

    Article  Google Scholar 

  3. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. Mach. Learn. Res. 3, 993–1022 (2003)

    MATH  Google Scholar 

  4. Brooks, L.R., Norman, G.R., Allen, S.W.: Role of specific similarity in a medical diagnostic task. J. Exp. Psychol. 120(3), 278–287 (1991)

    Article  Google Scholar 

  5. Chi, M.T.H., Feltovich, P.J., Glaser, R.: Categorization and representation of physics problems by experts and novices. Cognit. Sci. 5(2), 121–152 (1981)

    Article  Google Scholar 

  6. Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by latent semantic analysis. Am. Soc. Inf. Sci. 41(6), 391–407 (1990)

    Article  Google Scholar 

  7. Díaz-Galiano, M.C., Martín-Valdivia, M.T., Ureña-López, L.A.: Query expansion with a medical ontology to improve a multimodal information retrieval system. Comput. Biol. Med. 39(4), 396–403 (2009). https://doi.org/10.1016/j.compbiomed.2009.01.012

    Article  Google Scholar 

  8. Dib, E.G., Kidd, M.R., Saltman, D.C.: Case reports and the fight against cancer. J. Med. Case Rep. 2(1), 39 (2008). https://doi.org/10.1186/1752-1947-2-39

    Article  Google Scholar 

  9. Efron, B.: Bootstrap methods: another look at the jackknife. Ann. Stat. 7(1), 1–26 (1979)

    Article  MathSciNet  Google Scholar 

  10. Elstein, A.S.: Clinical problem solving and diagnostic decision making: selective review of the cognitive literature. BMJ 324(7339), 729–732 (2002). https://doi.org/10.1136/bmj.324.7339.729

    Article  Google Scholar 

  11. Greenes, A.R., Octo Barnett, G., Klein, S.W., Robbins, A., Prior, R.E.: Recording, retrieval and review of medical data by physician-computer interaction. N. Engl. J. Med. 282(6), 307–315 (1970). https://doi.org/10.1056/NEJM197002052820605

    Article  Google Scholar 

  12. Kidd, M., Hubbard, C.: Introducing journal of medical case reports. J. Med. Case Rep. 1(1), 1 (2007). https://doi.org/10.1186/1752-1947-1-1

    Article  Google Scholar 

  13. Klein, G.: Naturalistic decision making. Hum. Factors J. Hum. Factors Ergonomics Soc. 50(3), 456–460 (2008). https://doi.org/10.1518/001872008X288385

    Article  Google Scholar 

  14. Kolodner, J.L., Kolodner, R.M.: Using experience in clinical problem solving: introduction and framework. IEEE Trans. Syst. Man Cybern. 17(3), 420–431 (1987)

    Article  Google Scholar 

  15. Le, Q., Mikolov, T.: Distributed representations of sentences and documents. In: International Conference on Machine Learning, vol. 32, pp. 1188–1196 (2014). https://doi.org/10.1145/2740908.2742760

  16. León-Villagrá, P., Jäkel, F.: Categorization and abstract similarity in chess. In: Proceedings of the 35th Annual Meeting of the Cognitive Science Society, pp. 2860–2865. Cognitive Science Society, Berlin (2013). https://escholarship.org/uc/item/4jr8r7x1

  17. Linhares, A., Brum, P.: Understanding our understanding of strategic scenarios: what role do chunks play? Cognit. Sci. 31(6), 989–1007 (2007). https://doi.org/10.1080/03640210701703725

    Article  Google Scholar 

  18. Manning, C.D., Raghavan, P., Schütze, H.: Evaluation of unranked retrieval sets. In: Introduction to Information Retrieval, vol. 8, pp. 154–157. Cambridge University Press, Cambridge (2008)

    Google Scholar 

  19. Manning, C.D., Raghavan, P., Schütze, H.: Scoring, term weighting and the vector space model. In: Introduction to Information Retrieval, vol. 6, pp. 117–120. Cambridge University Press, Cambridge (2008)

    Google Scholar 

  20. Mason, R.A.: The case report - an endangered species? Anaesthesia 56(2), 99–102 (2001)

    Article  MathSciNet  Google Scholar 

  21. Medin, D.L., Goldstone, R.L., Gentner, D.: Respects for similarity. Psychol. Rev. 100(2), 254–278 (1993). https://doi.org/10.1037/0033-295X.100.2.254

    Article  Google Scholar 

  22. Medin, D.L., Schaffer, M.M.: Context theory of classification learning. Psychol. Rev. 85(3), 207–238 (1978). https://doi.org/10.1037/0033-295X.85.3.207

    Article  Google Scholar 

  23. Nissen, T., Wynn, R.: The clinical case report: a review of its merits and limitations. BMC Res. Notes 7(1), 264 (2014). https://doi.org/10.1186/1756-0500-7-264

    Article  Google Scholar 

  24. Sandu, N., Chowdhury, T., Schaller, B.J.: How to apply case reports in clinical practice using surrogate models via example of the trigeminocardiac reflex. J. Med. Case Rep. 10(1), 84 (2016). https://doi.org/10.1186/s13256-016-0849-z

    Article  Google Scholar 

  25. Spearman, C.: The proof and measurement of association between two things. Am. J. Psychol. 15(1), 72 (1904). https://doi.org/10.2307/1412159

    Article  Google Scholar 

  26. Tange, H.J., Schouten, H.C., Kester, A.D.M., Hasman, A.: The granularity of medical narratives and its effect on the speed and completeness of information retrieval. J. Am. Med. Inform. Assoc. 5(6), 571–582 (1998). https://doi.org/10.1136/jamia.1998.0050571

    Article  Google Scholar 

  27. Williams, D.D.R.: In defence of the case report. R. Coll. Psychiatr. 184(1), 84–88 (2004)

    MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. PSIORI, Freiburg, Germany

    Philipp Andreas Hummel, Frank Jäkel & Sascha Lange

  2. Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany

    Philipp Andreas Hummel

  3. Department for Haematology and Oncology, University Hospital Freiburg, Freiburg, Germany

    Roland Mertelsmann

Authors
  1. Philipp Andreas Hummel
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  2. Frank Jäkel
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  3. Sascha Lange
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  4. Roland Mertelsmann
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Corresponding author

Correspondence to Philipp Andreas Hummel .

Editor information

Editors and Affiliations

  1. Wright State University, Dayton, OH, USA

    Michael T. Cox

  2. Mälardalen University, Västeras, Sweden

    Peter Funk

  3. Mälardalen University, Västeras, Sweden

    Shahina Begum

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Hummel, P.A., Jäkel, F., Lange, S., Mertelsmann, R. (2018). A Textual Recommender System for Clinical Data. In: Cox, M., Funk, P., Begum, S. (eds) Case-Based Reasoning Research and Development. ICCBR 2018. Lecture Notes in Computer Science(), vol 11156. Springer, Cham. https://doi.org/10.1007/978-3-030-01081-2_10

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  • DOI: https://doi.org/10.1007/978-3-030-01081-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01080-5

  • Online ISBN: 978-3-030-01081-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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