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A Framework for Patient Data Management and Analysis in Randomised Clinical Trials

机译:随机临床试验中患者数据管理和分析的框架

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The efficient management and analysis of patient data enrolled in clinical studies is a critical factor for both supporting data management and knowledge discovery from data. Recent trends in literature present many approaches that demonstrate that the integration of multiple data sources (e.g. biochemical parameters, geographical data as well as the behaviour of patients into social networks) may improve the quality of findings. Moreover, the collection of such data may enable the development of a tailored intervention for precision medicine. All these aspects rely on the design and development of novel solutions for data management, storing and consequently, analysis. We here report the design and development of a prototype for data management and sharing introduced during a collaboration of Bioinformatics Laboratory, the Fisiopatology Unit and the University Hospital of Catanzaro. Our findings are currently under the validation of the clinicians.
机译:注册临床研究的患者数据的有效管理和分析是支持数据管理和从数据的知识发现的关键因素。文学的最新趋势存在许多方法,证明了多个数据源的整合(例如生物化学参数,地理数据以及患者的行为进入社交网络)可能会提高结果的质量。此外,这些数据的集合可以使得能够在精密药物中进行定制干预。所有这些方面都依赖于新型数据管理解决方案的设计和开发,储存,从而进行分析。我们在此报告了在生物信息学实验室,发病学单位和卡塔扎罗大学医院的协作期间引入了数据管理和共享的原型的设计和开发。我们的调查结果目前正在临床医生的验证。

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