Active and interactive analysis of prescription data for harm minimisation

积极和互动的处方数据分析，以减少危害。本计划旨在加强处方监察，以减少及预防不当用药对市民造成的危害。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。预期的结果包括对大规模处方数据的在线交互式分析，以及一个可以与卫生专业人员互动的系统，以提供高质量的实时处方监测，从而改善患者的治疗结果和医疗保健系统的效率。

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.