CLINICAL MONITORING USING REGRESSION-BASED TREND TEMPLATES

Our computer program TrenDx detects clinically significant trends in t ime-ordered patient data by matching data to patterns called trend tem plates, denoting multivariate temporal and value variation in normalit y and in disease. Previously a purely constraint-based TrenDx diagnose d 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. Im provement required resolving outstanding representational issues. In t his paper we describe regression-based trend templates, updated TrenDx algorithms, and their application to monitoring intensive care unit a nd pediatric growth data. We focus on new results in diagnosing pediat ric growth trends, and discuss potential application domains for TrenD x.