Active and interactive analysis of prescription data for harm minimisation

对处方数据进行主动和交互式分析，以最大限度地减少伤害

• 批准号: LP160100722
• 负责人: A/Prof Marcus Gallagher
• 金额: $ 13.27万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-12-14 至 2020-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP160100722
• 关键词: Active; interactive; analysis; prescription; data

Active and interactive analysis of prescription data for harm minimisation. This project aims to enhance prescription monitoring to reduce and prevent dangers to the public from inappropriate drug use. The project will develop a framework integrating active machine learning, interactive data mining, and data visualization into analysis of prescription data. The expected outcomes include online interactive analysis of large scale prescription data and a system that can interact with health professionals to provide high quality real time prescription monitoring, thereby improving patient outcomes and the efficiency of the healthcare system.

处方数据的主动和交互式分析，以最大限度地减少危害。该项目旨在加强对处方的监测，以减少和防止不适当使用药物对公众造成的危险。该项目将开发一个框架，将主动机器学习，交互式数据挖掘和数据可视化集成到处方数据分析中。预期成果包括大规模处方数据的在线交互分析，以及可以与卫生专业人员交互的系统，以提供高质量的真实的时间处方监测，从而改善患者的结果和医疗保健系统的效率。