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Issue 1, 2012
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Identification of fluid and substrate chemistry based on automatic pattern recognition of stains

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Abstract

This study proposes that images of stains from 100-nanolitre drops can be automatically identified as signatures of fluid composition and substrate chemistry, for e.g. rapid biological testing. Two datasets of stain images are produced and made available online, one with consumable fluids, and the other with biological fluids. Classification algorithms are used to identify an unknown stain by measuring its similarity to representative examples of predefined categories. The accuracy ranges from 80 to 94%, compared to an accuracy by random assignment of 3 to 4%. Clustering algorithms are also applied to group unknown stain images into a number of clusters each likely to correspond to similar combinations of fluids and substrates. The clustering accuracy ranges from 62 to 80%, compared to an accuracy by random assignment of 3 or 4%. The algorithms were also remarkably accurate at determining the presence or absence of biotin and streptavidin respectively in the liquid and on the glass, the salt composition, or the pH of the solution.

Graphical abstract: Identification of fluid and substrate chemistry based on automatic pattern recognition of stains

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Publication details

The article was received on 09 Jun 2011, accepted on 19 Sep 2011 and first published on 31 Oct 2011


Article type: Paper
DOI: 10.1039/C1AY05338H
Citation: Anal. Methods, 2012,4, 50-57
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    Identification of fluid and substrate chemistry based on automatic pattern recognition of stains

    N. Kim, Z. Li, C. Hurth, F. Zenhausern, S. Chang and D. Attinger, Anal. Methods, 2012, 4, 50
    DOI: 10.1039/C1AY05338H

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