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Improving the Diagnostic Performance of MUNIN by Remodelling of the Diseases

机译:通过疾病重塑提高MUNIN的诊断性能

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The paper describes a revision of the structure of MUNIN, a causal probabilistic network that specifies a stochastic model of the relations between a range of neuromuscular diseases and the findings associated with these diseases. The stochastic model was revised 1) to achieve a more flexible specification of the anatomical distribution of findings associated with the diseases, 2) to allow diagnosis of diseases or groups of diseases (e.g. polyneuropathies and motor neuron diseases) previously lumped under the common concept of diffuse neuropathy and 3) to model the correlation between carpal tunnel syndrome on the left and right side. Minor adjustments were also made to some of the conditional probabilities used to specify the pathophysiology of the diseases. The diagnostic capability of the revised model was evaluated by letting MUNIN diagnose 30 cases. The evaluation showed that the revised model performed better with a sensitivity of 94% and a specificity also of 94%.
机译:本文描述了MUNIN结构的修订版,MUNIN是一种因果概率网络,它指定了一系列神经肌肉疾病与与这些疾病相关的发现之间的关系的随机模型。修订了随机模型1),以实现与疾病相关的发现的解剖分布更灵活的规范; 2),允许诊断以前归类于以下常见概念的疾病或疾病组(例如,多发性神经病和运动神经元疾病) 3)建立左右腕管综合症之间的相关性模型。还对用于指定疾病的病理生理学的一些条件概率进行了较小的调整。通过让MUNIN诊断30例病例来评估修订模型的诊断能力。评估显示,修改后的模型表现更好,灵敏度为94%,特异性也为94%。

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