Selected article for: "approximate message and testing model"
Author: Junan Zhu; Kristina Rivera; Dror Baron
Title: Noisy Pooled PCR for Virus Testing
  • Document date: 2020_4_11
    • ID: f07zk05y_6
    Snippet: Contributions and organization. We focus on a simple pooled testing model for RT-PCR (Sec. II). This model is converted to a linear inverse problem (Sec. II-A), and our goal is to estimate a vector of patient illness status, x, from a vector of noisy RT-PCR measurements, y, a matrix A relating patients and measurements, and statistical information about false positives and negatives (Sec. II-B and Fig. 1 ). This estimation problem is solved using.....
    Document: Contributions and organization. We focus on a simple pooled testing model for RT-PCR (Sec. II). This model is converted to a linear inverse problem (Sec. II-A), and our goal is to estimate a vector of patient illness status, x, from a vector of noisy RT-PCR measurements, y, a matrix A relating patients and measurements, and statistical information about false positives and negatives (Sec. II-B and Fig. 1 ). This estimation problem is solved using generalized approximate message passing (GAMP) [7] in Sec. III. Promising numerical results are provided in Sec. IV, and Sec. V discusses how our GAMP-based approach can be extended.

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