David Gefen
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Abstract
Text analysis can reveal patterns of association among medical terms and medical codes.
- Beel, J., Gipp, B., Langer, S., and Breitinger, C. Research-paper recommender systems: A literature survey. International Journal on Digital Libraries 17, 4 (Nov. 2016), 305--338. Google Scholar
Digital Library
- Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., and Harshman, R. Indexing by latent semantic analysis. Journal of the American Society for Information Science 41, 6 (1990), 391--407.Google ScholarCross Ref
- Evangelopoulos, N., Zhang, X., and Prybutok, V.R. Latent semantic analysis: Five methodological recommendations. European Journal of Information Systems 21, 1 (Jan. 2012), 70--86.Google ScholarCross Ref
- Gefen, D., Endicott, J., Fresneda, J., Miller, J., and Larsen, K.R. A guide to text analysis with latent semantic analysis in R with annotated code studying online reviews and the Stack Exchange community. Communications of the Association for Information Systems 41, 21 (Dec. 2017), 450--496.Google ScholarCross Ref
- Gefen, D. and Larsen, K. Controlling for lexical closeness in survey research: A demonstration on the technology acceptance model. Journal of the Association for Information Systems 18, 10 (Oct. 2017), 727--757.Google ScholarCross Ref
- Gomez, J.C., Boiy, E., and Moens, M.-F. Highly discriminative statistical features for email classification. Knowledge Information Systems 31, 1 (Apr. 2012), 23--53.Google ScholarCross Ref
- Holzinger, A., Plass, M., Holzinger, K., Crisan, G.C., Pintea, C.-M., and Palade, V. A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop; https://arxiv.org/abs/1708.01104Google Scholar
- Holzinger, A., Schantl, J., Schroettner, M., Seifert, C., and Verspoor, K. Biomedical text mining: State-of-the-art, open problems and future challenges. Chapter in Interactive Knowledge Discovery and Data Mining Biomedical Informatics, Lecture Notes in Computer Science LNCS 8401, A. Holzinger and I. Jurisica, Eds. Springer, Berlin, Heidelberg, Germany, 2014, 271--300.Google Scholar
- Islam, A., Milios, E., and Keselj, V. Text similarity using Google tri-grams. In Proceedings of the 25<sup>th</sup> Canadian Conference on Artificial Intelligence (Toronto, Canada, May 28--30). Springer, Toronto, Canada, 2012, 312--317. Google ScholarDigital Library
- Kintsch, W. Predication. Cognitive Science 25, 2 (2001), 173--202.Google ScholarCross Ref
- Landauer, T.K. and Dumais, S.T. A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review 104, 2 (1997), 211--240.Google ScholarCross Ref
- Landauer, T.K., Foltz, P.W., and Laham, D. An introduction to latent semantic analysis. Discourse Processes 25, 2 and 3 (1998), 259--284.Google ScholarCross Ref
- Landauer, T.K., Laham, D., and Derr, M. From paragraph to graph: Latent semantic analysis for information visualization. Proceedings of the National Academy of Sciences 101, 1 (Apr. 6, 2004), 5214--5219.Google ScholarCross Ref
- Larsen, K.R. and Bong, C.H. A tool for addressing construct identity in literature reviews and meta-analyses. MIS Quarterly 40, 3 (Sept. 2016), 529--551. Google ScholarDigital Library
- Larsen, K.R., Michie, S., Hekler, E.B., Gibson, B., Spruijt-Metz, D., Ahern, D., Cole-Lewis, H., Ellis, R.J.B., Hesse, B., Moser, R.P., and Yi, J. Behavior change interventions: The potential of ontologies for advancing science and practice. Journal of Behavioral Medicine 40, 1 (Feb. 2017), 6--22.Google ScholarCross Ref
- Valle-Lisboa, J.C. and Mizraji, E. The uncovering of hidden structures by latent semantic analysis. Information Sciences 177, 19 (Oct. 2007), 4122--4147. Google ScholarDigital Library
- Zhiwei, H., Meiping, C., Jimin, W., Qing, S., Chao, Y., Xing, D., and Zhonggao, W. Improved control of hypertension following laparoscopic fundoplication for gastroesophageal reflux disease. Frontiers of Medicine 11, 1 (Mar. 2017), 68--73.Google Scholar
Index Terms
- Identifying patterns in medical records through latent semantic analysis
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