Continuous process improvement through workstation feedback for General Practice medicine using experts-in-the-loop data mining

该项目研究了数据挖掘结果的迭代使用，使专家能够构建反馈以影响后续的生产工作。我们在全科医学的背景下探讨这个问题，让全科医生（gp）审查他们自己的电子医疗记录和作者反馈的新模式，以阻止不良模式。这项工作将立即适用于医疗实践，并将推动数据挖掘方法的创新，特别是在有效识别时间和复杂的生态位模式方面。更广泛地说，这项工作将扩展数据挖掘用于创建工作站行为新期望的方式。

This project investigates the iterative use of data mining results to allow experts to construct feedback to influence subsequent production work. We explore the problem in the context of General Practice medicine by having General Practitioners (GPs) review emerging patterns from their own practice's electronic medical records and author feedback to discourage undesirable patterns. The work will have immediate applicability to medical practice and will drive innovation in data mining method, notably for efficient identification of temporal and complex niche patterns. More broadly, the work will extend the way data mining is used to create new expectations of workstation behaviour.