Division of Biomedical Informatics, School of Medicine, University California San Diego, 9500 Gilman Drive #0505, La Jolla, CA 92093-0505, USA.
Artif Intell Med. 2013 May;58(1):1-13. doi: 10.1016/j.artmed.2013.02.003. Epub 2013 Mar 22.
While EIRA has proved to be successful in the detection of anomalous patient responses to treatments in the Intensive Care Unit, it could not describe to clinicians the rationales behind the anomalous detections. The aim of this paper is to address this problem.
Few attempts have been made in the past to build knowledge-based medical systems that possess both argumentation and explanation capabilities. Here we propose an approach based on Dung's seminal calculus of opposition.
We have developed a new tool, arguEIRA, which is an extension of the existing EIRA system. In this paper we extend EIRA by providing it with an argumentation-based justification system that formalizes and communicates to the clinicians the reasons why a patient response is anomalous.
Our comparative evaluation of the EIRA system against the newly developed tool highlights the multiple benefits that the use of argumentation-logic can bring to the field of medical decision support and explanation.
虽然 EIRA 已被证明在检测重症监护病房中异常患者对治疗的反应方面非常成功,但它无法向临床医生描述异常检测背后的原理。本文旨在解决这一问题。
过去曾有一些尝试来构建具有论证和解释能力的基于知识的医学系统。在这里,我们提出了一种基于 Dung 开创性的对立演算的方法。
我们开发了一种新工具,即 arguEIRA,它是现有 EIRA 系统的扩展。在本文中,我们通过为 EIRA 提供基于论证的理由系统来扩展它,该系统将正式化并向临床医生传达为什么患者反应异常的原因。
我们对 EIRA 系统与新开发工具的比较评估突出了论证逻辑的使用可以为医疗决策支持和解释领域带来的多种好处。