@INPROCEEDINGS { Rsds3526,
author = {Stefanowski, Jerzy and Slowinski, Krzysztof}, 
title = {On Limitations of Using Rough Set Approach to Analyze Non-Trivial Medical Information Systems}, 
booktitle = {Proceedings of the Fourth International Workshop on Rough Sets, Fuzzy Sets, and Machine Discovery}, 
conference = {International Workshop on Rough Sets, Fuzzy Sets, and Machine Discovery}, 
pages = {176--183}, 
publisher = {Japanese Research Group on Rough Sets}, 
address = {Tokyo, Japan}, 
month = {November}, 
year = 1996, 
editor = {Tsumoto, Shusaku and Kobayashi, Satoshi and Yokomori, Takashi and Tanaka, Hiroshi and Nakamura, Akira}, 
isbn = {4-947717-01-7}, 
abstract = {The rough set theory has been used to analyze medical experience with urolithiasis patients treated by extracorporeal shock wave lithotripsy (ESWL). The aim of this analysis was to evaluate the significance of attributes for two classifications expressing the patients' condition after the ESWL treatment and to discover strong decision rules representing classification patterns interesting for practitioner. The ESWL information system is an example of a non-trivial medical data set where the use of a simple rough set model gives a high number of possible reducts being difficult to interpret. Two heuristic strategies based on the rough set theory are proposed. They lead to the selection of the most significant attributes consistent with clinical interpretation. Inducing only discriminating decision rules gives rules which are weak and too specific. Discovery of partly discriminating rules allows to extract rules supported by the larger number of cases. }, 
keywords = {rough sets, data mining, medical information systems, urolithiasis, }, 
}