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MACHINE LEARNING-BASED QUANTITATIVE ANALYSIS METHOD USING IMMUNO-WALL DEVICE

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We have newly designed antigen concentration estimation method utilizing machine learning technique on the immuno-wall device. Fluorescence intensities of one antigen detected under different amounts of capture antibody were combined into one combination, so that it can generate one unique pattern which is dependent on concentration of antigen (gradation immunoassay). In this research, 46,656 combinations were prepared by using 6 different concentrations of antigen and 5 different concentrations of capture antibody. Multivariate linear regression was conducted to estimate concentration of antigen using fluorescence intensities obtained under different amount of capture antibody as variables. As a result, comparison of the predictions to the actual antigen concentrations were drawn, and the coefficient of determination was 0.986. This method can provide accurate immunoassay result at on-site diagnosis.

Original languageEnglish
Title of host publicationMicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences
PublisherChemical and Biological Microsystems Society
Pages1161-1162
Number of pages2
ISBN (Electronic)9781733419048
Publication statusPublished - 2022
Externally publishedYes
Event26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022 - Hybrid, Hangzhou, China
Duration: 23-10-2022 → 27-10-2022

Publication series

NameMicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences

Conference

Conference26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022
Country/TerritoryChina
CityHybrid, Hangzhou
Period23-10-22 → 27-10-22

All Science Journal Classification (ASJC) codes

  • Chemical Engineering (miscellaneous)
  • Bioengineering
  • General Chemistry
  • Control and Systems Engineering

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