Genre
- Journal Article
The development and implementation of systems for real-time monitoring of health data has been limited in veterinary medicine by the lack of computerized, automatically collected data. We describe the construction of a surveillance system for early detection of cattle diseases based on laboratory requests, and explore algorithms for automated classification of data into syndromic groups. Classification rules resulted in high accuracy (99.95%), and allowed detailed documentation of the medical knowledge input in the model, improving communication with experts contributing to system development.
Dórea, F. C.: Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PE, C1A 4P3, Canada.
Maisons-Alfort; France
Association pour l'Étude de l'Épidémiologie des Maladies Animales
Language
- English
Subjects
- data logging
- diagnosis
- ruminants
- Canada
- animals
- surveillance
- eukaryotes
- Protozoan, Helminth, Mollusc and Arthropod Parasites of Animals (LL822) (New March 2000)
- Algorithms
- PEI
- Prion, Viral, Bacterial and Fungal Pathogens of Animals (LL821) (New March 2000)
- Disease surveys
- disease prevalence
- disease surveillance
- Diagnosis of Animal Diseases (LL886) (New March 2000)
- North America
- America
- Commonwealth of Nations
- Chordata
- Mathematics and Statistics (ZZ100)
- aetiology
- Artiodactyla
- OECD Countries
- information processing
- laboratory diagnosis
- Bovidae
- etiology
- APEC countries
- diagnostic techniques
- Information and Documentation (CC300)
- Prince Edward Island
- ungulates
- Developed Countries
- causal agents
- monitoring
- Data Collection
- mammals
- surveillance systems
- cattle diseases
- vertebrates
- Techniques and Methodology (ZZ900)
- Epidemiological surveys
- Epidemiology
- Bos
- cattle