Deep Learning‐Enabled Multiplexed Point‐of‐Care Sensor using a Paper‐Based Fluorescence Vertical Flow Assay

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Abstract
Multiplexed computational sensing with a point‐of‐care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury is demonstrated. This point‐of‐care sensor includes a paper‐based fluorescence vertical flow assay (fxVFA) processed by a low‐cost mobile reader, which quantifies the target biomarkers through trained neural networks, all within 0.9 linearity and <15% coefficient of variation. The competitive performance of this multiplexed computational fxVFA along with its inexpensive paper‐based design and handheld footprint makes it a promising point‐of‐care sensor platform that can expand access to diagnostics in resource‐limited settings.
Funding Information
  • National Science Foundation (#1648451)

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