Data Dialogue
Thursday, April 7, 2016, 11:45am, Gross 330
Alexander Chamessian
From EHR to insight: Using electronic health records to generate novel, non-intuitive hypotheses for translational research
Abstract:
Careful and perceptive clinical observations have frequently underpinned groundbreaking biomedical research. Many important research questions and subsequent discoveries have arisen from clinicians paying close attention to their patients. However, this approach is inherantly limited by the information-gathering and perceptual abilities of the human mind. The emergence of electronic health records (EHRs) and the concurrent advancement of statistical learning techniques now offers the opportunity scale up and enhance the "bedisde-to-bench" approach of the past. In this seminar, we will explore how application of data mining and statistical learning techniques to EHR data could be leveraged to generate novel hypotheses about disease mechanisms and associations, the insights from which could then be used to drive new experimental studies in the laboratory. We will discuss the potential application of this health data-driven approach in the context of chronic pain following major surgeries, such as thoractomy and amputation.

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