Abstract
The development of clinical practice guidelines is a difficult task. In most cases, it requires extensive elaboration of medical data repositories and tailoring of the corresponding results according to the medical setting under consideration. This tailoring should account for variations in diverse clinical settings. However, in any case, it has to be based on well-structured medical data patterns that provide experts with the necessary knowledge. Towards facilitating the overall task, this paper presents a computer-supported framework for the semi-automatic development of meaningful medical data patterns. The proposed framework comprises a novel hybrid methodology, which exploits decision trees features, and a web-based system that has been developed to accommodate this methodology. The overall framework pays much attention to the issues of user-friendliness, accuracy of results and visualization of the produced patterns.
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Fountoulaki, A., Karacapilidis, N., Manatakis, M. (2010). Using Decision Trees for the Semi-automatic Development of Medical Data Patterns: A Computer-Supported Framework. In: Lazakidou, A. (eds) Web-Based Applications in Healthcare and Biomedicine. Annals of Information Systems, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1274-9_16
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DOI: https://doi.org/10.1007/978-1-4419-1274-9_16
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