Pixel-Based Machine Learning and Image Reconstitution for Dot-ELISA Pathogen Diagnosis in Biological Samples.

Using the selected model, the R, G, B variable coefficients ± SEM were all found to be highly significant ( p < 10 −8 ) and estimated at β 1 = 0.080 ± 0.0152, β 2 = −0.722 ± 0.0174, β 3 = 0.543 ± 0.0140, respectively, implying a minor contribution of the R variable to positive pixel predictability and a substantial but reciprocal effect of the G and B variables.

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