costing; data mining; distributed processing; health care; insurance data processing; ACOs; HealthSCOPE; Microsoft Azure infrastructure; PMML; Spark MLLib; accountable care organizations; back-end system; cloud based prediction services; future cost prediction; healthcare cost estimation; healthcare scalable cost prediction engine; historical claims data; historical healthcare costs; interactive data mining framework; interactive distributed data mining framework; nondistributed environments; population based view; predictive model markup language; present day healthcare costs; Computational modeling; Data mining; Data models; Medical services; Predictive models; Sociology; Statistics; Healthcare cost prediction; Microsoft Azure; PMML; Spark; distributed data mining; insurance claims data;
机译:A Distributed Framework for Large-scale Protein-protein Interaction Data Analysis and Prediction Using MapReduce
机译:A Distributed Framework for Large-scale Protein-protein Interaction Data Analysis and Prediction Using MapReduce
机译:使用源匿名方案改进医疗服务,隐私保留分布式医疗保健数据收集和采矿
机译:从异构医疗数据存储库进行分布式数据挖掘:朝着基于智能代理的框架发展
机译:可伸缩的分布式数据挖掘模型的框架。
机译:在隐私约束下挖掘医疗数据的分布式集成方法
机译:用于成本敏感数据挖掘的完全分布式框架