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We demonstrate a low-cost and rapid paper-based vertical flow assay (VFA) for quantification of C-Reactive Protein (CRP). We use deep learning-based analysis of this VFA and its multiplexed sensing channels to achieve accurate quantification, as well as to overcome fabrication and operational variations along with limitations borne out of the hook effect, validating our results with clinical samples. This computational point-of-care test could be used for stratification of patients into cardiovascular disease risk assessment groups following standard clinical cut-offs. It can also broadly serve as a computational sensing platform for future point-of-care sensing and diagnostic applications.
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