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

页码：128 / 130

页数：3

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