Abstract
Quantitative databases are limited to information identified as important by their creators, while databases containing natural language are limited by our ability to analyze large unstructured bodies of text. Leximancer is a tool that uses semantic mapping to develop concept maps from natural language. We have applied Leximancer to educational based pathology case notes to demonstrate how real patient records or databases of case studies could be analyzed to identify unique relationships. We then discuss how such analysis could be used to conduct quantitative analysis from databases such as the Coronary Heart Disease Database. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Watson, M., Smith, A., & Watter, S. (2005). Leximancer concept mapping of patient case studies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3683 LNAI, pp. 1232–1238). Springer Verlag. https://doi.org/10.1007/11553939_171
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