Knowledge Graph: Applications in Tracing the Source of Large-Scale Outbreak — Beijing Municipality, China, 2020–2021 Article Swipe

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Ying Shen , Yonghong Liu , Xiaokang Jiao , Yuxin Cai , Xiang Xu , Hui Yao , Xiaoli Wang ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.46234/ccdcw2023.017

The KG model is a promising tool for predicting and controlling future COVID-19 epidemic waves and other infectious disease pandemics. By automatically inferring the source of infection, limited resources can be used efficiently to detect potential risks, allowing for rapid outbreak control.

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Infectious Diseases (Medical Specialty)

Artificial Intelligence

Theoretical Computer Science

Archaeology

Histopathology

Concepts

Outbreak Beijing Contact tracing Tracing Transmission (telecommunications) Inference Pandemic China Graph Infectious disease (medical specialty) Computer science Coronavirus disease 2019 (COVID-19) Geography Virology Disease Biology Medicine Artificial intelligence Theoretical computer science Telecommunications Archaeology Operating system Pathology

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Type: article
Language: en
Landing Page: https://doi.org/10.46234/ccdcw2023.017
PDF: https://weekly.chinacdc.cn/en/article/pdf/preview/10.46234/ccdcw2023.017
OA Status: diamond
Cited By: 2
References: 9
Related Works: 10
OpenAlex ID: https://openalex.org/W4318191021

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DOI: https://doi.org/10.46234/ccdcw2023.017

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Title: Knowledge Graph: Applications in Tracing the Source of Large-Scale Outbreak — Beijing Municipality, China, 2020–2021

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Type: article

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Language: en

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Publication year: 2023

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Publication date: 2023-01-01

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Authors: Ying Shen, Yonghong Liu, Xiaokang Jiao, Yuxin Cai, Xiang Xu, Hui Yao, Xiaoli Wang

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Landing page: https://doi.org/10.46234/ccdcw2023.017

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Concepts: Outbreak, Beijing, Contact tracing, Tracing, Transmission (telecommunications), Inference, Pandemic, China, Graph, Infectious disease (medical specialty), Computer science, Coronavirus disease 2019 (COVID-19), Geography, Virology, Disease, Biology, Medicine, Artificial intelligence, Theoretical computer science, Telecommunications, Archaeology, Operating system, Pathology

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Cited by: 2

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Citations by year (recent): 2025: 1, 2024: 1

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