A Treatment Decision Modeling and Optimizing Technology

治疗决策建模与优化技术

• 批准号: 6601515
• 负责人: HAO YING
• 金额: $ 14.66万
• 依托单位: WAYNE STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2006-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6601515
• 关键词: AIDS; AIDS therapy; HIV infections; Internet; clinical research; computer program /software; computer system design /evaluation; decision making; human data; information systems; patient care planning; physicians; statistics /biometry

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.

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，提出了一种新的与疾病无关的决策优化技术。 前者技术至关重要，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、主观且具有不确定性，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组件和状态的复杂系统。 所提出的新技术本质上是灵活的、动态的和高效的，这是由于其独特的能力，即对于任何疾病，在组件模型中复杂地表示关于患者和治疗的大量复杂信息，然后使用它们来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，它允许容易的知识更新和快速治疗策略的演变。 我们的初步研究为所提出的技术建立了部分理论基础。 在这个为期三年的试点阶段项目中，将建立对一般疾病进行治疗决策和优化的可行性、原则和结构。 为了验证和完善所提出的技术的理论和结构发展，并确定其临床效用，建立的结构将被用作实施艾滋病毒/艾滋病治疗决策系统的系统模板。该系统将使用我们的艾滋病毒/艾滋病数据库进行回顾性测试，该数据库包含2 200名患者。 将使用统计方法评估系统的初步准确性和实用性。 在项目结束时，科学界将可通过因特网获得两个在微软视窗中运行的软件包，用于研究目的。 其中一个将是一个通用的治疗决策系统，可针对特定疾病进行定制。 另一个是艾滋病毒/艾滋病治疗决策。 本项目所开发的技术和软件将为未来更严格、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，该技术可以为任何给定的患者提供优化的治疗决策。 它可用于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顾性的。