A combination of 'pooling' with a prediction model can reduce by 73% the\n number of COVID-19 (Corona-virus) tests

2020/05/03 by Tomer Cohen, Cohen, Tomer, Lior Finkelman +11
Medicine · Computer Science · #COVID-19 diagnosis using AI #Anomaly Detection Techniques and Applications

paper · pdf · doi:10.48550/arxiv.2005.03453

Abstract

We show that combining a prediction model (based on neural networks), with a\nnew method of test pooling (better than the original Dorfman method, and better\nthan double-pooling) called 'Grid', we can reduce the number of Covid-19 tests\nby 73%.\n

Citations

• The Detection of Defective Members of Large Populations

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