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Fuzzy One-Decision Making Model with Fuzzified Outcomes in the Treatment of Necrotizing Fasciitis

机译:虚拟化成果的模糊单决策模型治疗坏死性筋膜炎

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By proposing a new approach to fuzzy decision making, we try to support the medical decision, concerning recommendations for the treatment with hyperbaric oxygen (HBO). This treatment can be used for patients, suffering from necrotizing fasciitis. Due to the disease rarity, it sometimes is difficult for a physician to determine, if a single patient needs the treatment with HBO. We thus identify the decision with a linguistic variable, equipped with treatment recommendation levels. The choice of the appropriate level is based on values of clinical symptoms, found in the patient. To extract the optimal recommendation level for the treatment with HBO, we involve fuzzy set techniques in the decision model. In the paper, we mainly concentrate on designs of fuzzy sets, standing for clinical symptoms and recommendation levels. The levels act as the outcomes, dependent on the cumulative input of the patient's clinical markers. Since the focus is laid on a parametric structure of the outcomes, then we can categorize the model as robust approach to algorithmic modeling of outcomes, being part of eHealth data records.
机译:通过提出一种模糊决策的新方法,我们试图支持医学决定,关于用高压氧(HBO)治疗的建议。这种治疗可用于患者,患有坏死性筋膜炎。由于疾病稀有性,如果单个患者需要用HBO治疗,则难以确定医生。因此,我们用语言变量确定了配备治疗建议水平的决定。适当水平的选择是基于患者中发现的临床症状的值。为了提取HBO治疗的最佳推荐水平,我们涉及决策模型中的模糊集技术。在论文中,我们主要集中在模糊套装设计中,占临床症状和推荐水平。水平作为结果,依赖于患者临床标志物的累积输入。由于焦点是奠定了结果的参数结构,因此我们可以将模型作为结果的算法建模的鲁棒方法进行分类,是电子保健数据记录的一部分。

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