Syndromic surveillance using veterinary laboratory diagnostic test requests

被引：0
作者：
Dorea, F. C. [1 ]
Muckle, C. A. [2 ]
Kelton, D. [3 ]
McEwen, B. J. [4 ]
McNab, W. B. [5 ]
Sanchez, J. [1 ]
Revie, C. [1 ]
机构：
[1] Univ Prince Edward Isl, Atlantic Vet Coll, Dept Hlth Management, Charlottetown, PE C1A 4P3, Canada
[2] Univ Prince Edward Isl, Dept Pathol & Microbiol, Charlottetown, PE C1A 4P3, Canada
[3] Univ Guelph, Dept Populat Med, Guelph, ON N1G 2W1, Canada
[4] Univ Guelph, Hlth Anim Lab, Guelph, ON N1H 6R8, Canada
[5] Ontario Minist Agr Food & Rural Affairs, Guelph, ON N1G 4Y2, Canada
来源：
EPIDEMIOLOGIE ET SANTE ANIMALE, NO 59-60 | 2011年 / 59-60卷
关键词：
syndromic surveillance; cluster detection; aberration detection; time series; classification; laboratory-based surveillance; BIOTERRORISM;
D O I：
暂无
中图分类号：
S85 [动物医学（兽医学）];
学科分类号：
0906 ;
摘要：
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.
引用
收藏
页码：128 / 130
页数：3
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