摘要翻译：
精准医学是当代医学实践中最重要的范式转变，但在证据形成和临床实践实施方面存在诸多挑战。精确/个性化循证医学(pEBM)需要决策和信息管理的理论支持。本研究旨在提供所需的方法框架。广义相似证据理论主要建立在广义不确定性理论的基础上，广义不确定性理论将信息作为广义约束而不是有限的统计数据来管理；疾病原型相似理论在与原型（疾病的最佳例子）有相似关系时定义疾病/条件。该理论解释了精确个性化的证据结构是作为对特定研究问题的广义约束而形成的，约束关系涉及研究的平均效应大小及其与零假设的比较；可能是概率性的，也可能是可能性的。相似性度量被用来处理高维特征的比较。提供了Meta分析及其临床应用的实例。这是在医学中引入一个框架的第一次尝试之一，该框架在形成的证据的可推广性和研究人群的同质性之间提供了最佳的平衡。
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英文标题：
《Generalized Resemblance Theory of Evidence: a Proposal for
  Precision/Personalized Evidence-Based Medicine》
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作者：
Maani Beigy
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最新提交年份：
2015
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  Precision medicine emerges as the most important contemporary paradigm shift of medical practice but has several challenges in evidence formation and implementation for clinical practice. Precision/Personalized evidence-based medicine (pEBM) requires theoretical support for decision making and information management. This study aims to provide the required methodological framework. Generalized Resemblance Theory of Evidence mainly rests upon Generalized Theory of Uncertainty which manages information as generalized constraints rather than limited statistical data, and also Prototype Resemblance Theory of Disease which defines diseases/conditions when there is a similarity relationship with prototypes (best examples of the disease). The proposed theory explains that precisely-personalized structure of evidence is formed as a generalized constraint on particular research questions, where the constraining relation deals with averaged effect sizes of studies and its comparison to null hypothesis; which might be of either probabilistic or possibilistic nature. Similarity measures were employed to deal with comparisons of high-dimensional characteristics. Real examples of a meta-analysis and its clinical application are provided. This is one of the first attempts for introducing a framework in medicine, which provides optimal balance between generalizability of formed evidence and homogeneity of studied populations.
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PDF链接：
https://arxiv.org/pdf/1512.03825