Decision Support System for Medical Applications

R. Podraza, A. Dominik, and M. Walkiewicz (Poland)


Expert system, knowledge-based system, decisionsupport, rough set theory, data elimination.


The paper presents an idea of complex data analyses and decision support system for medical staff. The main goal of this system is to provide an easy to use, commonly available tool for quick diagnosing diseases, suggesting possible further treatment and deriving unknown dependences between different data coming from various patient's examinations. The system is based on the rough set theory [1] [2] [3]. In this paper the main stress is put on general idea of this system, the way it may be used and the fashion it works. What is more, the sketch of possible architecture of such system is presented including some example algorithms and suggested solutions, which may be applied during implementation. The prototype system has just been set up. The unique feature of the system relies on removing some data from decision tables [4] [5] to enhance the quality of generated rules. Usually such a data is discarded, because it is useless (or even harmful) in knowledge acquisition. In our approach the improper data (excluded from the data used for drawing conclusions) is carefully taken into considerations. This methodology can be very important in medical applications. A case not fitting to the general classification cannot be neglected, but should be examined with a special care.

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