Positive-unlabeled learning to infer protection status and identify correlates in vaccine efficacy field trials-Reference-Cited by-同舟云学术

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Positive-unlabeled learning to infer protection status and identify correlates in vaccine efficacy field trials

Published:2024-03 Issue:3 Volume:27 Page:109086
ISSN:2589-0042
Container-title:iScience
language:en
Short-container-title:iScience

Author:

Xu Shiwei,Kelkar Natasha S.,Ackerman Margaret E.^ORCID

Funder

National Institute of Allergy and Infectious Diseases

Publisher

Elsevier BV

Reference48 articles.

1. A Covid-19 Milestone Attained - A Correlate of Protection for Vaccines;Gilbert;N. Engl. J. Med.,2022

2. Nomenclature for immune correlates of protection after vaccination;Plotkin;Clin. Infect. Dis.,2012

3. Correlates of Vaccine- Induced Protection: Method and Implications,2013

4. A government-led effort to identify correlates of protection for COVID-19 vaccines;Koup;Nat. Med.,2021

5. Next Steps for Efficacy Evaluation in Clinical Trials of COVID-19 Vaccines;Jiang;Eng. Plast.,2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Leveraging permutation testing to assess confidence in positive-unlabeled learning applied to high-dimensional biological datasets;BMC Bioinformatics;2024-06-19

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