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An argument-based approach to reasoning with clinical knowledge

机译:基于论点的临床知识推理方法

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摘要

Better use of biomedical knowledge is an increasingly pressing concern for tackling chal lenging diseases and for generally improving the quality of healthcare. The quantity of biomedical knowledge is enormous and it is rapidly increasing. Furthermore, in many areas it is incomplete and inconsistent. The development of techniques for representing and reasoning with biomedical knowledge is therefore a timely and potentially valuable goal. In this paper, we focus on an important and common type of biomedical knowledge that has been obtained from clinical trials and studies. We aim for (1) a simple language for representing the results of clinical trials and studies; (2) transparent reasoning with that knowledge that is intuitive and understandable to users; and (3) simple computation mechanisms with this knowledge in order to facilitate the development of viable implementations. Our approach is to propose a logical language that is tailored to the needs of representing and reasoning with the results of clinical trials and studies. Using this logical language, we generate arguments and counterarguments for the relative merits of treat ments. In this way, the incompleteness and inconsistency in the knowledge is analysed via argumentation. In addition to motivating and formalising the logical and argumentation aspects of the framework, we provide algorithms and computational complexity results.
机译:更好地利用生物医学知识已成为解决棘手疾病和普遍提高医疗质量的日益紧迫的问题。生物医学知识的数量巨大并且正在迅速增加。此外,在许多领域它是不完整和不一致的。因此,开发用于表示和推理生物医学知识的技术是一个及时且可能有价值的目标。在本文中,我们重点研究从临床试验和研究中获得的重要且常见的生物医学知识类型。我们的目标是(1)用一种简单的语言来表示临床试验和研究的结果; (2)具有用户直观易懂的知识的透明推理; (3)具有此知识的简单计算机制,以便于开发可行的实现。我们的方法是提出一种逻辑语言,该语言适合于根据临床试验和研究结果来表示和推理的需求。使用这种逻辑语言,我们为处理的相对优点生成了参数和反参数。通过这种方式,通过论证来分析知识的不完整和不一致。除了激励和形式化框架的逻辑和论证方面,我们还提供算法和计算复杂性结果。

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