论文标题
多目标半监督聚类，以识别受伤患者的健康服务模式
Multi-objective semi-supervised clustering to identify health service patterns for injured patients
论文作者
论文摘要
这项研究开发了一种模式识别方法，该方法根据模式的相似性以及与感兴趣的结果的关联来识别模式。开发这种模式识别方法的实际目的是在伤害后早期阶段在交通事故中受伤的患者组。该分组基于伤害后第一周内卫生服务使用的独特模式。这些小组还提供有关药物过程总成本的预测信息。结果，患有不良结果的患者组被尽早确定为基于卫生服务的使用模式。
This study develops a pattern recognition method that identifies patterns based on their similarity and their association with the outcome of interest. The practical purpose of developing this pattern recognition method is to group patients, who are injured in transport accidents, in the early stages post-injury. This grouping is based on distinctive patterns in health service use within the first week post-injury. The groups also provide predictive information towards the total cost of medication process. As a result, the group of patients who have undesirable outcomes are identified as early as possible based health service use patterns.
