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Fuzzy Logic Model based on the Differential Nursing Diagnosis of Alterations in Urinary Elimination

机译:基于鉴别护理诊断尿辨率变化的模糊逻辑模型

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The nursing diagnoses associated with alterations in urinary elimination require different interventions, and nurses who are not specialists need support to diagnose and to manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for making differential diagnosis of alterations in urinary elimination, considering the nursing diagnosis approved by the North American Nursing Diagnosis Association (NANDA), 2001-2002,. The fuzzy maximum-minimum composition was used to develop this model. It was tested with 195 cases from a database of a previous study, The model was able to determine the diagnosis in total accordance with a panel of three experts for 79,5% of the cases. The model diagnosed 19% of the cases with partial concordance with the panel of experts. Only for 3 cases (1.5%) the model showed a different diagnosis. It is concluded that the model proposed here, despite of its simplicity, presents good performance. However, it is recommended more tests before widely used as support for clinical decision.
机译:在尿排除改变相关的护理诊断需要不同的干预措施,和护士谁不是专家需要支持来诊断和消除尿液的干扰管理的患者。这项研究的目的是基于模糊逻辑使尿消除改变的鉴别诊断,考虑到北美护理诊断协会(南大),2001 - 2002年批准的护理诊断提出一个模型,。模糊最大 - 最小组合物用于开发该模型。它与先前的研究数据库195箱子测试,该模型能够确定在总按照三位专家对病例79.5%面板诊断。该模型确诊病例19%与专家小组一致的部分。仅3例(1.5%)的模型表现出不同的诊断。结论提出的模型在这里,尽管它的简单,表现出良好的性能。但是,建议更多的测试前,广泛用于临床决策支持。

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