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医学信息学与临床决策:科学与实用方法

Medical informatics and clinical decision making: the science and the pragmatics.

作者信息

Shortliffe E H

机构信息

Section of Medical Informatics, Stanford University School of Medicine, CA 94305-5479.

出版信息

Med Decis Making. 1991 Oct-Dec;11(4 Suppl):S2-14.

PMID:1837576
Abstract

There are important scientific and pragmatic synergies between the medical decision making field and the emerging discipline of medical informatics. In the 1970s, the field of medicine forced clinically oriented artificial intelligence (AI) researchers to develop ways to manage explicit statements of uncertainty in expert systems. Classic probability theory was considered and discussed, but it tended to be abandoned because of complexities that limited its use. In medical AI systems, uncertainty was handled by a variety of ad hoc models that simulated probabilistic considerations. To illustrate the scientific interactions between the fields, the author describes recent work in his laboratory that has attempted to show that formal normative models based on probability and decision theory can be practically melded with AI methods to deliver effective advisory tools. In addition, the practical needs of decision makers and health policy planners are increasingly necessitating collaborative efforts to develop a computing and communications infrastructure for the decision making and informatics communities. This point is illustrated with an example drawn from outcomes management research.

摘要

医学决策领域与新兴的医学信息学学科之间存在着重要的科学和实用协同效应。在20世纪70年代,医学领域促使面向临床的人工智能(AI)研究人员开发管理专家系统中不确定性明确陈述的方法。经典概率论得到了考虑和讨论,但由于其复杂性限制了其应用,最终往往被放弃。在医学人工智能系统中,不确定性由各种模拟概率考量的临时模型来处理。为了说明这些领域之间的科学互动,作者描述了其实验室最近的工作,该工作试图表明基于概率和决策理论的形式化规范模型可以与人工智能方法实际融合,以提供有效的咨询工具。此外,决策者和卫生政策规划者的实际需求越来越需要各方共同努力,为决策和信息学社区开发计算和通信基础设施。这一点通过一个来自结果管理研究的例子加以说明。

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