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

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

Serological methods serve as a direct or indirect means of pathogen infection diagnosis in plant and animal species, including humans. Dot-ELISA (DE) is an inexpensive and sensitive, solid-state version of the microplate enzyme-linked immunosorbent assay, with a broad range of applications in epidem...

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Bibliographic Details
Main Authors: Cleo Anastassopoulou, Athanasios Tsakris, George P. Patrinos, Yiannis Manoussopoulos
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Microbiology
Subjects:
dot-blot ELISA
machine learning
image analysis
serological assays
sensitivity and specificity
ROC curve
Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2021.562199/full

Internet

https://www.frontiersin.org/articles/10.3389/fmicb.2021.562199/full

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