医学的实践性、疾病的个体性导致误诊率居高不下,而基于人工智能和医学大数据的临床决策支持系统(clinical decision support system,CDSS)能在疾病诊断时为医生提供决策支持,成为解决此类问题的一个重要手段,且现已取得一定的成效。不...医学的实践性、疾病的个体性导致误诊率居高不下,而基于人工智能和医学大数据的临床决策支持系统(clinical decision support system,CDSS)能在疾病诊断时为医生提供决策支持,成为解决此类问题的一个重要手段,且现已取得一定的成效。不过,尽管CDSS在提高医疗决策的准确性和效率方面具有潜在优势,但其在实施过程中也存在一系列的问题,这些问题可能影响CDSS的可靠性、可用性和安全性。本文对诊断类CDSS的应用现状、面临的挑战和未来发展趋势进行总结分析,以期对我国CDSS向智能化和知识化方向发展提供参考。展开更多
随着信息技术的迅速发展,智能决策支持系统(IDSS)在企业管理中的应用日益受到关注。本文旨在探讨IDSS在企业管理中的应用,分析其当前存在的问题并给出解决措施。首先介绍了IDSS的背景和意义,阐述了其在生产运营、市场营销、供应链管理...随着信息技术的迅速发展,智能决策支持系统(IDSS)在企业管理中的应用日益受到关注。本文旨在探讨IDSS在企业管理中的应用,分析其当前存在的问题并给出解决措施。首先介绍了IDSS的背景和意义,阐述了其在生产运营、市场营销、供应链管理等领域的具体应用场景,并强调了其对企业决策的重要性。然后分析了IDSS面临的挑战,包括数据质量、模型不确定性等问题,并提出了利用大数据、人工智能等新技术来解决这些问题的解决方案。通过本文,可以更深入地理解IDSS在企业管理中的作用,为企业决策者提供理论指导和实践建议。With the rapid development of information technology, the application of Intelligent Decision Support Systems (IDSS) in enterprise management is attracting increasing attention. This paper aims to explore the role and impact of IDSS in enterprise management, analyze the current problems it faces, and provide solutions. The background and significance of Intelligent Decision Support Systems (IDSS) are first introduced, elucidating its specific application scenarios in areas such as production operations, marketing, and supply chain management, emphasizing its crucial role in business decision-making. Subsequently, the challenges faced by IDSS are analyzed, including issues like data quality and model uncertainty, with proposed solutions leveraging new technologies, such as big data and artificial intelligence. This aims to provide a deeper understanding of IDSS’s role in enterprise management, offering theoretical guidance and practical recommendations to facilitate continuous business development and innovation. Through this paper, a deeper understanding of the role of IDSS in enterprise management can be gained, providing theoretical guidance and practical advice for business decision-makers.展开更多
文摘医学的实践性、疾病的个体性导致误诊率居高不下,而基于人工智能和医学大数据的临床决策支持系统(clinical decision support system,CDSS)能在疾病诊断时为医生提供决策支持,成为解决此类问题的一个重要手段,且现已取得一定的成效。不过,尽管CDSS在提高医疗决策的准确性和效率方面具有潜在优势,但其在实施过程中也存在一系列的问题,这些问题可能影响CDSS的可靠性、可用性和安全性。本文对诊断类CDSS的应用现状、面临的挑战和未来发展趋势进行总结分析,以期对我国CDSS向智能化和知识化方向发展提供参考。
文摘随着信息技术的迅速发展,智能决策支持系统(IDSS)在企业管理中的应用日益受到关注。本文旨在探讨IDSS在企业管理中的应用,分析其当前存在的问题并给出解决措施。首先介绍了IDSS的背景和意义,阐述了其在生产运营、市场营销、供应链管理等领域的具体应用场景,并强调了其对企业决策的重要性。然后分析了IDSS面临的挑战,包括数据质量、模型不确定性等问题,并提出了利用大数据、人工智能等新技术来解决这些问题的解决方案。通过本文,可以更深入地理解IDSS在企业管理中的作用,为企业决策者提供理论指导和实践建议。With the rapid development of information technology, the application of Intelligent Decision Support Systems (IDSS) in enterprise management is attracting increasing attention. This paper aims to explore the role and impact of IDSS in enterprise management, analyze the current problems it faces, and provide solutions. The background and significance of Intelligent Decision Support Systems (IDSS) are first introduced, elucidating its specific application scenarios in areas such as production operations, marketing, and supply chain management, emphasizing its crucial role in business decision-making. Subsequently, the challenges faced by IDSS are analyzed, including issues like data quality and model uncertainty, with proposed solutions leveraging new technologies, such as big data and artificial intelligence. This aims to provide a deeper understanding of IDSS’s role in enterprise management, offering theoretical guidance and practical recommendations to facilitate continuous business development and innovation. Through this paper, a deeper understanding of the role of IDSS in enterprise management can be gained, providing theoretical guidance and practical advice for business decision-makers.
