Mapping of clinical data from cattle to data from pathology reports to gain information for surveillance of animal diseases through text and data mining
Contact Person: John Berezowski
duration: 2017 - 2019
Early detection of animal disease epidemics is critical for animal and public health. To be effective, early detection surveillance should monitor data from many sources. Apart from clinical data, veterinary pathology records are an important source, but information is often in text documents and unsuitable for analyses. In a previous project, a text mining tool was successfully developed to extract data from post-mortem reports from the University of Bern for surveillance. Clinical data from health services for livestock and breeder organizations are an additional source of data to be used. Due to the differences in nomenclature, these data sources cannot be combined. The purpose of this project is to: 1) Expand the text mining tool to analyze and combine both pathology and clinical data, 2) Develop tools to extract information from both sources and use spatial-temporal event detection algorithms to identify spatial clusters 3) develop an interface which enriches pathological reports with terminological information.
