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Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project

机译:应用知识锚定的假设发现方法推进临床和转化研究:OAMiner项目

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摘要

The conduct of clinical and translational research regularly involves the use of a variety of heterogeneous and large-scale data resources. Scalable methods for the integrative analysis of such resources, particularly when attempting to leverage computable domain knowledge in order to generate actionable hypotheses in a high-throughput manner, remain an open area of research. In this report, we describe both a generalizable design pattern for such integrative knowledge-anchored hypothesis discovery operations and our experience in applying that design pattern in the experimental context of a set of driving research questions related to the publicly available Osteoarthritis Initiative data repository. We believe that this ‘test bed’ project and the lessons learned during its execution are both generalizable and representative of common clinical and translational research paradigms.
机译:临床和转化研究的开展定期涉及各种异构和大规模数据资源的使用。对于此类资源进行综合分析的可伸缩方法,尤其是在尝试利用可计算领域知识以高通量方式生成可行假设的方法时,仍然是一个开放的研究领域。在本报告中,我们既描述了这种集成的知识锚定假设发现操作的通用设计模式,又描述了我们在与公开可用的骨关节炎倡议数据库相关的一组驾驶研究问题的实验环境中应用该设计模式的经验。我们认为,这个“试验床”项目及其执行过程中吸取的教训既可以推广,又可以代表常见的临床和转化研究范式。

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