In medical diagnosis, how to select an optimal medicine from some medicines with similar efficacy values to treat diseases has become common problems between doctors and patients. To solve this problem, we describe it as a multi-attribute decision-making (MADM) in a finite fuzzy covering approximation space. This paper aims to propose two pairs of covering-based variable precision fuzzy rough sets. By combining the proposed rough set model with the VIKOR method, we construct a novel method to medicine selection MADM problems in the context of medical diagnosis. A real-life case study of selecting a proper medicine to treat Alzheimer’s disease is given to demonstrate the practicality of our proposed method. Through a comparative analysis and an experimental analysis, we further explore the effectiveness and stability of the established method.

中文翻译：

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基于覆盖的可变精度模糊粗糙集的MADM方法：在医学诊断中的应用

在医学诊断中，如何从具有相似功效值的某些药物中选择最佳药物来治疗疾病已成为医患之间的普遍问题。为了解决此问题，我们将其描述为有限模糊覆盖近似空间中的多属性决策（MADM）。本文旨在提出两对基于覆盖的变精度模糊粗糙集。通过将提出的粗糙集模型与VIKOR方法相结合，我们构造了一种在医学诊断中针对医学选择MADM问题的新方法。一个现实的案例研究，选择合适的药物来治疗阿尔茨海默氏病，以证明我们提出的方法的实用性。通过比较分析和实验分析，我们进一步探索了所建立方法的有效性和稳定性。