Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation
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چکیده
منابع مشابه
Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation.
Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and spec...
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BACKGROUND Syndromic surveillance research has focused on two main themes: the search for data sources that can provide early disease detection; and the development of efficient algorithms that can detect potential outbreak signals. METHODS This work combines three algorithms that have demonstrated solid performance in detecting simulated outbreak signals of varying shapes in time series of l...
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Today, a great deal of data is generated in the medical field. Acquiring useful knowledge from this raw data requires data processing and detection of meaningful patterns and this objective can be achieved through data mining. Using data mining to diagnose and prognose heart diseases has become one of the areas of interest for researchers in recent years. In this study, the literature on the ap...
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Introduction The New York State Veterinary Diagnostic Laboratory (NYSVDL) receives more than 100,000 diagnostic submissions a year that are not currently used in any formal syndromic surveillance system. In 2009, a pilot study of syndrome classification schemes was undertaken and in 2011 a new general submission form was adopted, which includes a check list of syndromes, as part of the clinical...
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ژورنال
عنوان ژورنال: Journal of The Royal Society Interface
سال: 2013
ISSN: 1742-5689,1742-5662
DOI: 10.1098/rsif.2013.0114