Semi-quantitative Classification of HIV-1 Nucleic Acids Using ResNet Image Analysis of Discretized Isothermal Amplification Reactions in a Microfluidic Chip
Coleman D. Martin, Noah Charles Benson, Nandini Gummalla, Kelli N. Shimazu, AT Bender, DAC Beck, Jonathan D. Posner
This paper develops a machine learning approach to semi-quantitatively classify HIV-1 nucleic acids using image analysis of isothermal amplification reactions in microfluidic chips, achieving high accuracy across a wide concentration range.
bioRxiv · Jun 24, 2026 · PreprintBioengineering