Unsupervised subjects classification using insulin and glucose data for insulin resistance assessment

Unsupervised subjects classification using insulin and glucose data for insulin resistance assessment

In this paper, the ?-means clustering algorithm is employed to perform an unsupervised classification of subjects based on unidimensional observations (HOMA-IR and the Matsuda indexes separately) and multidimensional observations (insulin and glucose samples obtained from the oral glucose tolerance...

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Библиографические подробности
Главный автор:	Wong De Balzan, Sara (author)
Формат:	article
Опубликовано:	2015
Online-ссылка:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962783931&doi=10.1109%2fSTSIVA.2015.7330444&partnerID=40&md5=99fb81f9bcf7f7759af9821e7f6faa0c http://dspace.ucuenca.edu.ec/handle/123456789/29209
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