School of Computer Science, Hubei University of Technology, Wuhan, China.
Network & Informatization Center, Wuhan Polytechnic University, Wuhan, China.
Math Biosci Eng. 2022 Jul 25;19(10):10445-10473. doi: 10.3934/mbe.2022489.
In clinical decision support, argumentation plays a key role while alternative reasons may be available to explain a given set of signs and symptoms, or alternative plans to treat a diagnosed disease. In literature, this key notion usually has closed boundary across approaches and lacks of openness and interoperability in Clinical Decision Support Systems (CDSSs) been built. In this paper, we propose a systematic approach for the representation of argumentation, their interpretation towards recommendation, and finally explanation in clinical decision support. A generic argumentation and recommendation scheme lays the foundation of the approach. On the basis of this, argumentation rules are represented using Resource Description Framework (RDF) for clinical guidelines, a rule engine developed for their interpretation, and recommendation rules represented using Semantic Web Rule Language (SWRL). A pair of proof knowledge graphs are made available in an integrated clinical decision environment to explain the argumentation and recommendation rationale, so that decision makers are informed of not just what are recommended but also why. A case study of triple assessment, a common procedure in the National Health Service of UK for women suspected of breast cancer, is used to demonstrate the feasibility of the approach. In conducting hypothesis testing, we evaluate the metrics of accuracy, variation, adherence, time, satisfaction, confidence, learning, and integration of the prototype CDSS developed for the case study in comparison with a conventional CDSS and also human clinicians without CDSS. The results are presented and discussed.
在临床决策支持中,论证起着关键作用,因为可能有其他原因可以解释给定的一组症状,或者有其他治疗已诊断疾病的方案。在文献中,这个关键概念通常在不同的方法之间有封闭的边界,缺乏开放性和互操作性,这在构建临床决策支持系统 (CDSS) 时是一个挑战。在本文中,我们提出了一种系统的方法来表示论证,解释论证以生成推荐,最终在临床决策支持中进行解释。一个通用的论证和推荐方案为该方法奠定了基础。在此基础上,使用资源描述框架 (RDF) 表示论证规则,为其解释开发了一个规则引擎,并使用语义 Web 规则语言 (SWRL) 表示推荐规则。在一个集成的临床决策环境中提供了一对证明知识图谱,以解释论证和推荐的基本原理,使决策者不仅了解推荐的内容,还了解推荐的原因。我们使用英国国民健康服务体系中对疑似乳腺癌女性进行的三联评估作为案例研究,演示了该方法的可行性。在进行假设检验时,我们评估了针对该案例研究开发的原型 CDSS 的准确性、变化、遵守、时间、满意度、信心、学习和集成等指标,与传统 CDSS 和没有 CDSS 的人类临床医生进行了比较。结果进行了呈现和讨论。