A Bayesian method for synthesizing multiple diagnostic outcomes of COVID-19 tests | Zendy

Lirong Cao | Zendy; Shi Zhao | Zendy; Qi Li | Zendy; Lowell Ling | Zendy; William Ka Kei Wu | Zendy; Lin Zhang | Zendy; Jingzhi Lou | Zendy; Ka Chun Chong | Zendy; Zigui Chen | Zendy; Eliza LaiYi Wong | Zendy; Benny Zee | Zendy; Matthew T.V. Chan | Zendy; Paul K.S. Chan | Zendy; Maggie Haitian Wang | Zendy

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A Bayesian method for synthesizing multiple diagnostic outcomes of COVID-19 tests

Author(s) -

Lirong Cao,

Shi Zhao,

Qi Li,

Lowell Ling,

William Ka Kei Wu,

Lin Zhang,

Jingzhi Lou,

Ka Chun Chong,

Zigui Chen,

Eliza LaiYi Wong,

Benny Zee,

Matthew T.V. Chan,

Paul K.S. Chan,

Maggie Haitian Wang

Publication year - 2021

Publication title -

royal society open science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.84

H-Index - 51

ISSN - 2054-5703

DOI - 10.1098/rsos.201867

Subject(s) - bayesian probability , computer science , outcome (game theory) , covid-19 , machine learning , probabilistic logic , posterior probability , sensitivity (control systems) , diagnostic test , artificial intelligence , data mining , medicine , disease , mathematics , engineering , pathology , infectious disease (medical specialty) , emergency medicine , mathematical economics , electronic engineering

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