Corpus ID: 218674391

A Compressed Sensing Approach to Group-testing for COVID-19 Detection

@article{Ghosh2020ACS,
  title={A Compressed Sensing Approach to Group-testing for COVID-19 Detection},
  author={Sabyasachi Ghosh and R. Agarwal and Mohammad Ali Rehan and Shreya Pathak and Pratyush Agrawal and Yash Gupta and Sarthak Consul and N. Gupta and Ritika Goyal and A. Rajwade and M. Gopalkrishnan},
  journal={arXiv: Quantitative Methods},
  year={2020}
}
We propose Tapestry, a novel approach to pooled testing with application to COVID-19 testing with quantitative Polymerase Chain Reaction (PCR) that can result in shorter testing time and conservation of reagents and testing kits. Tapestry combines ideas from compressed sensing and combinatorial group testing with a novel noise model for PCR. Unlike Boolean group testing algorithms, the input is a quantitative readout from each test, and the output is a list of viral loads for each sample. While… Expand

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