基于粗糙集的肉芽学检测疾病并发症的可能性

S. Tsumoto
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摘要

医学专家系统最重要的问题之一是它们不能对复杂病例做出鉴别诊断。本文从信息粒化的角度综述了并发症的推理,提出了一种从临床数据集中提取并发症诊断规则的方法。示例表明,基于粗糙集的颗粒计算为检测复杂性提供了一个很好的框架。
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Detecting possibility of complications of diseases using rough set based granulation
One of the most important problems with medical expert systems is that they cannot make a differential diagnosis with complicated cases. This paper reviews reasoning about complications from the viewpoint of information granulation and proposes an approach to extracting rules for diagnosis of complications from clinical datasets. The illustrative example show that rough set based granular computing gives a nice framework to detect the complications.
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