Medical Reasoning and Rough Sets

Authors:
Shusaku Tsumoto
Affiliations:
Department of Medical Informatics, Faculty of Medicine, Shimane University, 89-1 Enya-cho Izumo 693-8501, Japan
Venue:
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Year:
2007

Citing 5
Cited 0

Variable precision rough set model

Journal of Computer and System Sciences
From rough set theory to evidence theory

Advances in the Dempster-Shafer theory of evidence
Elements of machine learning

Elements of machine learning
Automated extraction of medical expert system rules from clinical databases based on rough set theory

Information Sciences: an International Journal
Modelling Medical Diagnostic Rules Based on Rough Sets

RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Pawlak showed that knowledge can be captured by data partition and proposed a rough set method where comparison between data partition gives knowledge about classification. Interestingly, thes approximations correspond to the focusing mechanism of differential medical diagnosis; upper approximation as selection of candidates and lower approximation as concluding a final diagnosis. This paper focuses on severl models of medical reasoning shows that core ideas of rough set theory can be observed in these diagnostic models.