Selected article for: "binary splitting and positive case"

Author: Cassidy Mentus; Martin Romeo; Christian DiPaola
Title: Analysis and Applications of Non-Adaptive and Adaptive Group Testing Methods for COVID-19
  • Document date: 2020_4_7
  • ID: 3sr4djft_54
    Snippet: This method is extended to populations with a random number of (+) cases by setting the upper limit on positive cases according a chosen condence level (i.e. the probability that the number of (+) exceeds this is very small). In probability terms, if the number of positive cases D is generated acccording to a probability distribution, and we assume probability c that will identify every positive case, then let D c be such that P (D ≤ D c ) < c......
    Document: This method is extended to populations with a random number of (+) cases by setting the upper limit on positive cases according a chosen condence level (i.e. the probability that the number of (+) exceeds this is very small). In probability terms, if the number of positive cases D is generated acccording to a probability distribution, and we assume probability c that will identify every positive case, then let D c be such that P (D ≤ D c ) < c. Generalized binary splitting is then applied to nd at most D c positive cases in the population.

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