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Prospects and Challenges in COVID-19 Study: A Review Based on Influencing Factors and Analysis Methods

Published: 04 December 2023 Publication History

Abstract

The unprecedented Coronavirus Disease 2019 had spread and diffused in many countries and regions worldwide, posing a serious threat to people's health and lives. This review presents a systematic analysis and summary of representative research on the role of AI technology in the prediction and containment of COVID-19 and influencing factors of its transmission. To further explore the influences of multiple factors on the incidence and transmission of COVID-19, we used total cases per million (TCPM) and total deaths per million (TDPM) as dependent variables and influencing factors as explanatory variables to conduct multiple linear regression, and constructed four training models: xgboost model (XGBR), random forest regenerator (RFR), extra trees regenerator (ETR), and gradient boosting regenerator (GBR) to predict the test data. This study highlights the contribution and application prospects of AI related technologies in the study of the spread of COVID-19, which will help deepen the global understanding of the COVID-19 pandemic, and provide a reference for curbing the wanton spread of COVID-19 and other diseases again.

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  1. Prospects and Challenges in COVID-19 Study: A Review Based on Influencing Factors and Analysis Methods

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    ICBDT '23: Proceedings of the 2023 6th International Conference on Big Data Technologies
    September 2023
    441 pages
    ISBN:9798400707667
    DOI:10.1145/3627377
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    Published: 04 December 2023

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    1. COVID-19
    2. artificial intelligence
    3. epidemic control
    4. machine learning
    5. risk factors

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