A decision support system using classification of the blood glucose and HbA1C level classes from palm perspiration data

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Summary

Artificial neural network structures were used for the classification of the relationship between blood data values and palm perspiration rate as a non-invasive measurement technique and a comparative study was realized by using feed forward multilayer, Elman, probabilistic, radial basis and learning vector quantisation neuralnetwork structures.

Type
article
Published
2012-05-02
Cited by
1
References
25

Keywords

Perspiration, Artificial neural network, Artificial intelligence, Support vector machine, Data set

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