Terenziani Paolo, Montani Stefania, Bottrighi Alesio, Torchio Mauro, Molino Gianpaolo
DISTA, Universita' del Piemonte Orientale, Amedeo Avogadro, Alessandria 15100, Italy.
Proc AMIA Symp. 2002:772-6.
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.
GLARE(指南获取、表示与执行)是一个与领域无关的系统,用于临床指南的获取、表示与执行。GLARE在支持面临指南中各种选择的用户/医生的决策过程的方法上独具特色。在许多情况下,最佳选择不能仅基于“局部信息”来确定(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替代路径的信息。GLARE通过“假设分析”工具,一种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(如成本、资源、时间)的假设推理形式,利用各种路径中可用的“全局信息”。特别是,处理时间信息这一极其复杂的任务涉及对人工智能(AI)社区开发的各种技术的扩展和改编。