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

, Frontiers Production Office

doi:10.3389/fmicb.2021.688832

ERRATUM article

Front. Microbiol., 27 April 2021

Sec. Microbial Immunology

Volume 12 - 2021 | https://doi.org/10.3389/fmicb.2021.688832

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

This article is an erratum on:

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

by Anastassopoulou, C., Tsakris, A., Patrinos, G. P., and Manoussopoulos, Y. (2021). Front. Microbiol. 12:562199. doi: 10.3389/fmicb.2021.562199

Due to a production error, two formulas were incorrectly published in the Materials and Methods section, subsection Step 2: Model Selection and Supervised Training of the Classifier Algorithm. The correct formulas are provided below.

\begin{array}{l} ln [\frac{π (x)}{1 - π (x)}] = α + β_{1} x_{R} + β_{2} x_{G} + β_{3} x_{B} + β_{4} x_{D i l} \\ π (x) = \frac{e^{α + β_{1} x_{R} + β_{2} x_{G} + β_{3} x_{B} + β_{4} x_{D i l}}}{1 + e^{α + β_{1} x_{R} + β_{2} x_{G} + β_{3} x_{B} + β_{4} x_{D i l}}} \end{array}

The publisher apologizes for this mistake. The original article has been updated.

Keywords: dot-blot ELISA, machine learning, image analysis, serological assays, sensitivity and specificity, ROC curve, diagnostic performance

Citation: Frontiers Production Office (2021) Erratum: Pixel-Based Machine Learning and Image Reconstitution for Dot-ELISA Pathogen Diagnosis in Biological Samples. Front. Microbiol. 12:688832. doi: 10.3389/fmicb.2021.688832

Received: 31 March 2021; Accepted: 31 March 2021;
Published: 27 April 2021.

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Frontiers Editorial Office, Frontiers Media SA, Switzerland

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

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