Predicting COVID-19 with AI techniques: current research and future directions

被引：0

作者：

Comito, Carmela ^{[1
]}

Pizzuti, Clara ^{[1
]}

机构：

[1] Natl Res Council Italy CNR, ICAR Inst, Via Pietro Bucci 8-9 C, Arcavacata Di Rende, CS, Italy

来源：

PROCEEDINGS OF THE 2021 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING, ASONAM 2021 | 2021年

关键词：

COVID-19; Artificial Intelligence; Machine Learning; Deep Learning; Forecasting;

D O I：

10.1145/3487351.3490958

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Artificial Intelligence (AI), since the onset of the COVID-19 pandemic at the beginning of the last year, is playing an important role in supporting physicians and health authorities in different difficult tasks such as virus spreading, patient diagnosing and monitoring, contact tracing. In this paper, we provide an overview of the methods based on AI technologies proposed for COVID-19 forecasting. Summary statistics of the techniques adopted by researchers, categorized on the base of the underlying AI sub-area, are reported, along with publication venue of papers. The effectiveness of these approaches is investigated and their capabilities or weaknesses in providing reliable predictions are discussed. Future challenges are finally analyzed and research directions for improving current tools are suggested.

引用

页码：518 / 524

页数：7

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