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BACKGROUND Large linked databases (LLDB) represent a novel resource for cancer outcomes research. However, accurate means of identifying a patient population of interest within these LLDBs can be challenging. Our research group developed a fully integrated platform that provides a means of combining independent legacy databases into a single cancer-focused(More)
Applications are increasingly being executed on computational systems that have hierarchical parallelism. There are several programming paradigms which may be used to adapt a program for execution in such an environment. In this paper , we outline some of the challenges in porting codes to such systems, and describe a programming environment that we are(More)
Applications are increasingly being executed on computational systems that have hierarchical parallelism. There are several programming paradigms which may be used to adapt a program for execution in such an environment. In this paper, we outline some of the challenges in porting codes to such systems, and describe a programming environment that we are(More)
Background: Large linked databases (LLDB) represent a novel resource for cancer outcomes research. However, accurate means of identifying a patient population of interest within these LLDBs can be challenging. Our research group developed a fully integrated platform that provides a means of combining independent legacy databases into a single cancer-focused(More)
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