Theory and Algorithm of Group Testing for Error Correction and Test Reduction
DOI:
https://doi.org/10.51094/jxiv.50Keywords:
Group Testing, Message PassingAbstract
Group testing is a method of reducing the number of tests by mixing multiple patient specimens. In this paper, we consider a problem setting in which Bayesian inference is used to identify patients' states from mixed specimens. We describe methods to evaluate the marginal posterior probabilities using the message passing algorithm, and to determine the cutoff value by introducing a risk function. We show that by choosing the cutoff value appropriately, false positives and false negatives of the original test can be corrected with a small number of tests when the prevalence is sufficiently small.
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Submitted: 2022-04-15 19:50:00 UTC
Published: 2022-04-19 06:07:44 UTC
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Ayaka Sakata
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