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- W2912806390 abstract "Diabetes is a group of metabolic disorders in which there are high blood sugar levels over a prolonged period. Type 2 DM begins with insulin resistance, a condition in which cells fail to respond to insulin properly. Diabetes type 2 accounts for about 90% of cases. Therefore, the development of new methods for the diagnosis of diabetes is relevant. In this article, the method of IR spectroscopy in combination with multidimensional analysis is proposed as a diagnostic method. Cluster analysis, partial least-squares (PLS) regression, principal component analysis (PCA) are performed to assess the correct diagnosis probability. Each of the three presented methods gives the best results when using the first derivative of the spectra in the whole range of the spectrum. Despite the fact that in this paper the PLS method differentiates samples with only 81% probability, the use of PLS methods is preferable, since in this case a training set of samples is used for which the desired characteristics are known." @default.
- W2912806390 created "2019-02-21" @default.
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- W2912806390 date "2018-12-01" @default.
- W2912806390 modified "2023-10-17" @default.
- W2912806390 title "Multivariate Analysis for Diagnostic of Type II Diabetes Mellitus" @default.
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- W2912806390 doi "https://doi.org/10.1109/iecbes.2018.8626635" @default.
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