An approach to use machine learning to optimize paper immunoassays for SARS-CoV-2 IgG and IgM antibodies

Author:

Mata Calidonio Josselyn1,Hamad-Schifferli Kimberly12ORCID

Affiliation:

1. Dept. of Engineering, University of Massachusetts Boston, Boston, MA 02125, USA

2. School for the Environment, University of Massachusetts Boston, Boston, MA 02125, USA

Abstract

Optimizing paper immunoassay conditions for diagnostic accuracy is often achieved by tuning running conditions in a trial and error manner. We report the use of machine learning to optimize an assay for SARS-CoV-2 IgG and IgM antibodies.

Funder

University of Massachusetts Boston

Publisher

Royal Society of Chemistry (RSC)

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