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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >A diagnostic reasoning and optimal treatment model for bacterial infections with fuzzy information.
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A diagnostic reasoning and optimal treatment model for bacterial infections with fuzzy information.

机译：具有模糊信息的细菌感染的诊断推理和最佳治疗模型。

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摘要

This study proposes an optimization model for optimal treatment of bacterial infections. Using an influence diagram as the knowledge and decision model, we can conduct two kinds of reasoning simultaneously: diagnostic reasoning and treatment planning. The input information of the reasoning system are conditional probability distributions of the network model, the costs of the candidate antibiotic treatments, the expected effects of the treatments, and extra constraints regarding belief propagation. Since the prevalence of the pathogens and infections are determined by many site-by-site factors, which are not compliant with conventional approaches for approximate reasoning, we introduce fuzzy information. The output results of the reasoning model are the likelihood of a bacterial infection, the most likely pathogen(s), the suggestion of optimal treatment, the gain of life expectancy for the patient related to the optimal treatment, the probability of coverage associated with the antibiotic treatment, and the cost-effect analysis of the treatment prescribed.
机译：这项研究提出了一种优化模型，用于细菌感染的最佳治疗。使用影响图作为知识和决策模型，我们可以同时进行两种推理：诊断推理和治疗计划。推理系统的输入信息是网络模型的条件概率分布，候选抗生素治疗的费用，治疗的预期效果以及有关信念传播的额外约束。由于病原体和感染的患病率是由许多逐点因素决定的，这些因素与常规的近似推理方法不符，因此我们引入了模糊信息。推理模型的输出结果是细菌感染的可能性，最可能的病原体，最佳治疗的建议，与最佳治疗相关的患者预期寿命的增加，与疾病相关的覆盖率抗生素治疗，以及所规定治疗的成本效果分析。

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