Medical knowledge induction with higher-order horn clauses and meta-programming

Authors:
Nittaya Kerdprasop;Natthapon Pannurat;Kittisak Kerdprasop
Affiliations:
Data Engineering and Knowledge Discovery Research Unit, School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand;Data Engineering and Knowledge Discovery Research Unit, School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand;Data Engineering and Knowledge Discovery Research Unit, School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand
Venue:
SMO'09 Proceedings of the 9th WSEAS international conference on Simulation, modelling and optimization
Year:
2009

Citing 11
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Abstract

Modern healthcare organizations generate huge amount of electronic data stored in heteogeneous database. Even though these data are a valuable resource for mining useful knowledge to support scientific decision making, a representational heterogeneity of such database requires a customized and flexible method to mine actionable knowledge. In this paper we propose a medical decision support system (MDSS) based on a logical framework. The proposed MDSS includes a knowledge induction component to induce knowledge from clinical data repositories and the induced knowledge can be deployed to pre-treatment data from other sources. The implementation of knowledge induction engine has been presented to express the power of higher-order programming of logic-based language. The flexibility of our mining engine is ontained through the pattern matching and meta-programming facilities provided by logic-based language.