Abstract
Generalization of the fundamental rough set discernibility tools aiming at searching for relevant patterns for complex decisions is discussed. As an example of application, there is considered the post-surgery survival analysis problem for the head and neck cancer cases. The goal is to express dissimilarity between different survival tendencies by means of clinical information. It requires handling decision values in form of plots representing the Kaplan-Meier product estimates for the groups of patients.
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Bazan, J., Skowron, A., Ślȩzak, D., Wróblewski, J. (2003). Searching for the Complex Decision Reducts: The Case Study of the Survival Analysis. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science(), vol 2871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39592-8_22
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DOI: https://doi.org/10.1007/978-3-540-39592-8_22
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