Exploratory Analysis of Methods for Automated Classification of Laboratory Test Orders into Syndromic Groups in Veterinary Medicine

摘要

BackgroundRecent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes–syndromic surveillance–using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users.