Fuzzy neighborhood rough set-based attribute reduction over temporal information systems with application to clinical efficacy evaluation

Xiaoxiao Chang

doi:10.1016/j.ipm.2026.104730

Fuzzy neighborhood rough set-based attribute reduction over temporal information systems with application to clinical efficacy evaluation

2026-03-13

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DOI：10.1016/j.ipm.2026.104730

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Abstract

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• The temporal Information Systems with Imbalanced, Incomplete, and Heterogeneous Attributes is constructed. • A Gaussian-kernel fuzzy neighborhood with multi-β covering is constructed. • Unsupervised indices and a unified Q objective drive reduction and weight learning. • State-space smoothing + FDR + EWMA enable three-trend efficacy discrimination. • The scientific and feasibility of the proposed method are verified from multiple perspectives.

Keywords:

Fuzzy neighborhood

Rough set

Attribute reduction

Temporal information systems

Clinical efficacy evaluation

Fuzzy neighborhood rough set-based attribute reduction over temporal information systems with application to clinical efficacy evaluation

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