Langlotz C P, Fagan L M, Tu S W, Sikic B I, Shortliffe E H
Comput Biomed Res. 1987 Jun;20(3):279-303. doi: 10.1016/0010-4809(87)90059-0.
Through our experience with the ONCOCIN cancer therapy consultation system, we have identified a set of medical planning problems to which no single existing computer-based reasoning technique readily applies. In response to the need for automated assistance with this class of problems, we have devised a computer program called ONYX that combines decision-theoretic and artificial intelligence approaches to planning. We discuss our rationale for devising a new planning architecture and describe in detail how that architecture is implemented. The program's planning process consists of three steps: (i) the use of rules derived from therapy planning strategies to generate a small set of plausible plans, (ii) the use of knowledge about the structure and behavior of the human body to create simulations that predict possible consequences of each plan for the patient, and (iii) the use of decision theory to rank the plans according to how well the results of each simulation meet the treatment goals. This architecture explicitly manages the uncertainty inherent in many planning tasks, introduces a possible mechanism for the dissemination of decision-theoretic therapy advice, and potentially increases the number of problem solving domains in which expert system techniques can be effectively applied.
通过我们在ONCOCIN癌症治疗咨询系统方面的经验，我们识别出了一类医学规划问题，现有的任何单一基于计算机的推理技术都难以直接应用于这些问题。为了满足对这类问题提供自动化辅助的需求，我们设计了一个名为ONYX的计算机程序，它将决策理论和人工智能方法结合用于规划。我们讨论了设计新规划架构的基本原理，并详细描述了该架构是如何实现的。该程序的规划过程包括三个步骤：(i) 使用从治疗规划策略导出的规则生成一小套合理的计划；(ii) 利用关于人体结构和行为的知识创建模拟，以预测每个计划对患者可能产生的后果；(iii) 使用决策理论根据每个模拟的结果满足治疗目标的程度对计划进行排序。这种架构明确管理了许多规划任务中固有的不确定性，引入了一种传播决策理论治疗建议的可能机制，并有可能增加可以有效应用专家系统技术的问题解决领域的数量。
