ROUGH SET BASED RULE INDUCTION APPROACH FOR SURVIVAL ANALYSIS
*Perumal Venkatesan
ABSTRACT
The boundaries in medical diagnosis and treatment are usually vague and imprecise. With vague information on
signs and symptoms the physicians diagnose a patient and decide on the best way to cure them. Rough set is a
leading soft computing method and its theory provides methods for knowledge extraction from imperfect data.
This paper deals with a rough set based new approach for survival analysis. The decision problem is formulated
over database on spinal tuberculosis patients treated under a randomized trial. The rule based method expresses the
difference between the expected outcomes under the different treatment groups. The rules for different survival
tendencies are also formulated using a prognostic index. The new frame work is combined with semi-parametric
survival models to identify survival patterns. The usefulness of the method is demonstrated using outcomes of the
trial.
Keywords: Rough set, rule induction, survival analysis, Kaplan-Meier, Cox model, spinal tuberculosis.
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