A Treatment Decision Modeling and Optimizing Technology

描述(由申请人提供)： 将模糊系统技术与离散事件系统技术相结合，提出了一种新的疾病无关决策与优化技术。前者是必要的，因为首先，许多症状、诊断和治疗结果不仅取决于患者，而且不精确、不可测量和具有不确定性的主观性，其次，必须利用临床医生的主观知识和经验。离散事件系统技术最适合处理具有众多部件和状态的复杂系统。拟议的新技术本质上是灵活、动态和高效的，因为它具有独特的能力，可以在组件模型中紧凑地表示任何疾病的大量关于患者和治疗的复杂信息，然后使用它们自动合成用于优化的整体治疗模型。这种模块化、自下而上的模式确保了针对不同疾病的决策系统在结构和设计上的相似性。此外，它允许轻松的知识更新和快速的治疗策略演变。 我们的初步研究已经为拟议的技术奠定了部分理论基础。在这一为期三年的试点阶段，将建立疾病治疗决策和总体优化的可行性、原则和结构。为了验证和完善拟议技术的理论和结构开发并确定其临床用途，所建立的结构将用作实施艾滋病毒/艾滋病治疗决策系统的系统模板。该系统将使用我们包含2,200名患者的艾滋病毒/艾滋病数据库进行追溯测试。将使用统计方法评估该系统的初步准确性和实用性。在该项目结束时，科学界将可以通过因特网获得在微软视窗系统中运行的两个软件包，用于研究目的。其中一个将是一个可针对特定疾病定制的通用治疗决策系统。另一项将用于艾滋病毒/艾滋病的治疗决策。 本项目开发的技术和软件将为今后更严格、更大规模地开发多种疾病的治疗决策系统奠定基础。一旦完全开发，这项技术可以为任何给定的患者做出优化的治疗决策。它可以用来客观和定量地分析和比较不同的治疗方案和选择，无论是前瞻性的还是回溯性的。

DESCRIPTION (provided by applicant): A novel disease-independent decision-making and optimization technology is proposed by combining fuzzy systems technology with discrete event systems technology. The former technology is essential because, first, many symptoms, diagnoses, and treatment outcomes are not only patient-dependent, but also imprecise, immeasurable, and subjective with uncertainty, and, second, a clinician's subjective knowledge and experience must be utilized. Discrete event systems technology is most suitable for handling complex systems with numerous components and states. The proposed new technology is intrinsically flexible, dynamic, and efficient due to its unique ability to compactly represent, for any disease, a large amount of complex information on patient and treatment in component models and then use them to automatically synthesize an overall treatment model for optimization. This modular, bottom-up paradigm ensures the structural and design similarity of decision systems for different diseases. Furthermore, it permits easy knowledge upgrade and fast treatment strategy evolution. Our preliminary study has established part of the theoretical foundation for the proposed technology. In this three-year pilot phase project, the feasibility, principle and structure for making treatment decision and optimization for diseases in general will be established. To validate and refine the theoretical and structural development of the proposed technology and determine its clinical utility, the established structure will be used as a system template for implementing an HIV/AIDS treatment decision system. The system will be tested retrospectively using our HIV/AIDS database containing 2,200 patients. Statistical methods will be used to assess the preliminary accuracy and utility of the system. At the end of the project, two software packages running in MS Windows will be available to the scientific community through the Internet for research purposes. One will be a generic treatment decision system that is customizable for a specific disease. The other will be for HIV/AIDS treatment decision-making. The technology and software developed in this project will lay the foundation for more rigorous and larger scale development of treatment decision systems for many diseases in the future. Once fully developed, the technology can produce optimized treatment decisions for any given patient. It can be used to objectively and quantitatively analyze and compare different treatment options and selections, either prospectively or retrospectively.