We have written a prototype computer program called TrenD_x for automated trend detection during process monitoring. The program uses a representation called trend templates that define disorders as typical patterns of relevant variables. These patterns consist of a partially ordered set of temporal intervals with uncertain endpoints. Bound to each temporal interval arc value constraints on real-valued functions of measurable parameters. TrenD_x has been used to diagnose trends in growth patterns from examining heights, weights and other parameters of pediatric patients. As TrenD_x analyzes successive data points, the program updates its hypotheses about which stage of the growth process each data point belongs to. We present an example of TrenD_x reaching temporally plausible diagnoses for an actual patient with delayed growth currently being seen at Boston Children's Hospital.
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