Channing H. Russell

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The objective of the work described in this paper is to develop a means for characterizing the validity of an empirical methodology for detecting signals potentially related to complicated adverse event (AE) coding terms in multidimensional public health surveillance data. The signal detection tool under evaluation is the multi-item gamma Poisson shrinkage(More)
Neural network visualization and learning algorithms provide an attractive approach to displaying clinical data and predicting patient outcomes. However, the raw data in medical databases is typically not in a form that permits easy application of such algorithms. For example, data may consist of scattered and noisy individual measurements that are(More)
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