Viral Load Inference in Non-Adaptive Pooled Testing
arxiv(2024)
摘要
Medical diagnostic testing can be made significantly more efficient using
pooled testing protocols. These typically require a sparse infection signal and
use either binary or real-valued entries of O(1). However, existing methods do
not allow for inferring viral loads which span many orders of magnitude. We
develop a message passing algorithm coupled with a PCR (Polymerase Chain
Reaction) specific noise function to allow accurate inference of realistic
viral load signals. This work is in the non-adaptive setting and could open the
possibility of efficient screening where viral load determination is clinically
important.
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