Decision Theoretic Cutoff and ROC Analysis for Bayesian Optimal Group Testing-Reference-Cited by-同舟云学术

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Decision Theoretic Cutoff and ROC Analysis for Bayesian Optimal Group Testing

Published:2023-09 Issue:9 Volume:69 Page:5902-5920
ISSN:0018-9448
Container-title:IEEE Transactions on Information Theory
language:
Short-container-title:IEEE Trans. Inform. Theory

Author:

Sakata Ayaka¹^ORCID,Kabashima Yoshiyuki²^ORCID

Affiliation:

1. Department of Statistical Inference and Mathematics, The Institute of Statistical Mathematics, Tachikawa, Japan

2. Department of Physics, Institute for Physics of Intelligence, Trans-Scale Quantum Science Institute, The University of Tokyo, Tokyo, Japan

Funder

Japanese Society for the Promotion of Science (JSPS) through the Grant-in-Aid for Scientific Research

CASIO Science Promotion Foundation

Japan Science and Technology Agency (JST) CREST

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/18/10225323/10124787.pdf?arnumber=10124787

Reference58 articles.

1. A new pooling strategy for high-throughput screening: the Shifted Transversal Design

2. Group Testing Regression Models with Fixed and Random Effects

3. A Method for Detecting all Defective Members in a Population by Group Testing

4. Bayesian Estimation of Disease Prevalence and the Parameters of Diagnostic Tests in the Absence of a Gold Standard

5. Noisy adaptive group testing using Bayesian sequential experimental design;cuturi;arXiv 2004 12508,2020

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