Paolo Terenziani, Stefania Montani, Alesio Bottrighi, Mauro Torchio, Gianpaolo Molino
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引用次数: 0
Abstract
GLARE (GuideLine Acquisition, Representation and Execution) is a domain-independent system for the acquisition, representation and execution of clinical guidelines. GLARE is unique in its approach to supporting the decision-making process of users/physicians faced with various alternatives in the guidelines. In many cases, the best alternative cannot be determined on the basis of "local information" alone (i.e., by considering just the selection criteria associated with the decision at hand), but must also take into account information stemming from relevant alternative pathways. Exploitation of "global information" available in the various pathways is made possible by GLARE through the "what if" facility, a form of hypothetical reasoning which allows users to gather relevant decision parameters (e.g., costs, resources, times) from selected parts of the guideline in a semi-automatic fashion. In particular, the extremely complex task of coping with temporal information involves the extension and adaptation of various techniques developed by the Artificial Intelligence (AI) community.
指南获取、表示和执行(GuideLine Acquisition, Representation and Execution)是一个独立于领域的系统,用于临床指南的获取、表示和执行。在支持用户/医生面对指南中各种替代方案的决策过程方面,眩光是独特的。在许多情况下,最佳备选方案不能仅根据“当地信息”确定(即,仅考虑与手头决策相关的选择标准),还必须考虑来自相关备选途径的信息。通过“假设”设施,可以利用各种途径中可用的“全球信息”,这是一种假设推理形式,允许用户以半自动方式从指南的选定部分收集相关决策参数(例如成本,资源,时间)。特别是,处理时间信息的极其复杂的任务涉及人工智能(AI)社区开发的各种技术的扩展和适应。