Clinical monitoring using regression-based trend templates

Our computer program TrenDx detects clinically significant trends in time-ordered patient data by matching data to patterns called trend templates, denoting multivariate temporal and value variation in normality and in disease. Previously a purely constraint-based TrenDx diagnosed pediatric growth trends and reached the same diagnoses as a panel of experts, at a time no later than the experts, in most of 30 cases. Improvement required resolving outstanding representational issues. In this paper we describe regression-based trend templates, updated TrenDx algorithms, and their application to monitoring intensive care unit and pediatric growth data. We focus on new results in diagnosing pediatric growth trends, and discuss potential application domains for TrenDx.