LAUSR

Grouping methods for estimating the prevalences of rare traits from complex survey data that preserve confidentiality of respondents.

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1 Published in 2018 at "Statistics in medicine"

DOI: 10.1002/sim.7648

Abstract: Originally, 2-stage group testing was developed for efficiently screening individuals for a disease. In response to the HIV/AIDS epidemic, 1-stage group testing was adopted for estimating prevalences of a single or multiple traits from testing… read more here.

Keywords: survey data; estimating prevalences; group testing; group ... See more keywords

Capturing the pool dilution effect in group testing regression: A Bayesian approach

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2 Published in 2022 at "Statistics in Medicine"

DOI: 10.1002/sim.9532

Abstract: Group (pooled) testing is becoming a popular strategy for screening large populations for infectious diseases. This popularity is owed to the cost savings that can be realized through implementing group testing methods. These methods involve… read more here.

Keywords: group; dilution effect; group testing; methodology ... See more keywords

Group testing regression analysis with covariates and specimens subject to missingness

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2 Published in 2023 at "Statistics in Medicine"

DOI: 10.1002/sim.9640

Abstract: We develop parametric estimators of a conditional prevalence in the group testing context. Group testing is applied when a binary outcome variable, often a disease indicator, is assessed by testing a specimen for the presence… read more here.

Keywords: testing regression; subject missingness; group; conditional prevalence ... See more keywords

Extended symbol correction algorithm for group testing based non-binary error correction codes of minimum distance d 

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1 Published in 2020 at "Microelectronics Reliability"

DOI: 10.1016/j.microrel.2020.113724

Abstract: Abstract This work presents a new decoding algorithm that extends the error-correction capacity of group testing based (GTB) non-binary error correction codes without modifying the number of parity symbols of the codeword. A list decoding… read more here.

Keywords: group testing; correction; error correction; non binary ... See more keywords

Noisy Adaptive Group Testing: Bounds and Algorithms

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1 Published in 2019 at "IEEE Transactions on Information Theory"

DOI: 10.1109/tit.2018.2883604

Abstract: The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly noisy tests, and is relevant in applications such as medical… read more here.

Keywords: group testing; bounds algorithms; testing bounds; adaptive group ... See more keywords

Sublinear-Time Non-Adaptive Group Testing With O(k log n) Tests via Bit-Mixing Coding

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1 Published in 2021 at "IEEE Transactions on Information Theory"

DOI: 10.1109/tit.2020.3046113

Abstract: The group testing problem consists of determining a small set of defective items from a larger set of items based on tests on groups of items, and is relevant in applications such as medical testing,… read more here.

Keywords: group testing; tex math; log; inline formula ... See more keywords

Performance Bounds for Group Testing With Doubly-Regular Designs

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1 Published in 2022 at "IEEE Transactions on Information Theory"

DOI: 10.1109/tit.2022.3210593

Abstract: In the group testing problem, the goal is to identify a subset of defective items within a larger set of items based on tests whose outcomes indicate whether any defective item is present. This problem… read more here.

Keywords: number; test; design; group testing ... See more keywords

Inverse sampling regression for pooled data

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1 Published in 2017 at "Statistical Methods in Medical Research"

DOI: 10.1177/0962280214568047

Abstract: Because pools are tested instead of individuals in group testing, this technique is helpful for estimating prevalence in a population or for classifying a large number of individuals into two groups at a low cost.… read more here.

Keywords: regression; group testing; sampling regression; inverse sampling ... See more keywords

Group testing as a strategy for COVID-19 epidemiological monitoring and community surveillance

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0 Published in 2021 at "PLoS Computational Biology"

DOI: 10.1371/journal.pcbi.1008726

Abstract: We propose an analysis and applications of sample pooling to the epidemiologic monitoring of COVID-19. We first introduce a model of the RT-qPCR process used to test for the presence of virus in a sample… read more here.

Keywords: covid epidemiological; strategy covid; group testing; group ... See more keywords

Blood Group Testing

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2 Published in 2022 at "Frontiers in Medicine"

DOI: 10.3389/fmed.2022.827619

Abstract: Red blood cell (RBC) transfusion is one of the most frequently performed clinical procedures and therapies to improve tissue oxygen delivery in hospitalized patients worldwide. Generally, the cross-match is the mandatory test in place to… read more here.

Keywords: blood groups; blood group; group testing; transfusion ... See more keywords

Dynamic Infection Spread Model Based Group Testing

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1 Published in 2022 at "Algorithms"

DOI: 10.3390/a16010025

Abstract: Group testing idea is an efficient approach to detect prevalence of an infection in the test samples taken from a group of individuals. It is based on the idea of pooling the test samples and… read more here.

Keywords: infection spread; infection; number; group ... See more keywords