PRELIMINARY DATA ANALYSIS IN HEALTHCARE MULTICENTRIC DATA MINING: A PRIVACY-PRESERVING DISTRIBUTED APPROACH
PRELIMINARY DATA ANALYSIS IN HEALTHCARE MULTICENTRIC DATA MINING: A PRIVACY-PRESERVING DISTRIBUTED APPROACH
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DOI：
10.20368/1971-8829/1454
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发表时间：
2018-01-01
影响因子：
1.1
通讯作者：
Valentini, Vincenzo
中科院分区：
文献类型：
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作者：
Damiani, Andrea;Masciocchi, Carlotta;Valentini, Vincenzo
认知医疗保健系统的新时代提供了大量的患者数据，可用于开发预测模型和临床决策支持系统。在这一框架内，大力鼓励采取多机构办法，以便收集更多的样本进行数据挖掘，并获得更可靠的统计数据。为了这些目的，需要为数据管理开发共享本体，以确保数据库语义一致性符合各个中心的伦理和法律的政策。因此，我们提出了一种隐私保护的分布式方法作为初步的数据分析工具，以确定可能的合规性问题和异质性，从商定的多机构研究协议之前，训练的临床预测模型。这种初步分析看起来快速可靠，其结果与使用传统的集中式方法获得的结果一致。还提供了一个真实的实时交互式仪表板来显示分析结果，并使工作流程更快捷、更轻松。
The new era of cognitive health care systems offers a large amount of patient data that can be used to develop prediction models and clinical decision support systems. In this frame, the multi-institutional approach is strongly encouraged in order to reach more numerous samples for data mining and more reliable statistics. For these purposes, shared ontologies need to be developed for data management to ensure database semantic coherence in accordance with the various centers' ethical and legal policies. Therefore, we propose a privacy-preserving distributed approach as a preliminary data analysis tool to identify possible compliance issues and heterogeneity from the agreed multi-institutional research protocol before training a clinical prediction model. This kind of preliminary analysis appeared fast and reliable and its results corresponded to those obtained using the traditional centralized approach. A real time interactive dashboard has also been presented to show analysis results and make the workflow swifter and easier.