کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
517577 | 867467 | 2007 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Unsupervised clustering of over-the-counter healthcare products into product categories
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Unsupervised clustering of over-the-counter healthcare products into product categories Unsupervised clustering of over-the-counter healthcare products into product categories](/preview/png/517577.png)
چکیده انگلیسی
A general problem in biosurveillance is finding appropriate aggregates of elemental data to monitor for the detection of disease outbreaks. We developed an unsupervised clustering algorithm for aggregating over-the-counter healthcare (OTC) products into categories. This algorithm employs MCMC over hundreds of parameters in a Bayesian model to place products into clusters. Despite the high dimensionality, it still performs fast on hundreds of time series. The procedure was able to uncover a clinically significant distinction between OTC products intended for the treatment of allergy and OTC products intended for the treatment of cough, cold, and influenza symptoms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Biomedical Informatics - Volume 40, Issue 6, December 2007, Pages 642–648
Journal: Journal of Biomedical Informatics - Volume 40, Issue 6, December 2007, Pages 642–648
نویسندگان
Garrick L. Wallstrom, William R. Hogan,