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

共 50 条

[21] Towards classification and comprehensive analysis of AI-based COVID-19 diagnostic techniques: A survey [J].

Kosar, Amna ;

Asif, Muhammad ;

Bin Ahmad, Maaz ;

Akram, Waseem ;

Mahmood, Khalid ;

Kumari, Saru .

ARTIFICIAL INTELLIGENCE IN MEDICINE, 2024, 151

[22] Overview of current state of research on the application of artificial intelligence techniques for COVID-19 [J].

Kumar, Vijay ;

Singh, Dilbag ;

Kaur, Manjit ;

Damasevicius, Robertas .

PEERJ COMPUTER SCIENCE, 2021,

[23] Overview of Current State of Research on the Application of Artificial Intelligence Techniques for COVID-19 [J].

Kumar V. ;

Singh D. ;

Kaur M. ;

Damaševičius R. .

PeerJ Computer Science, 2021, 7 :1-34

[24] AI in Thyroid Cancer Diagnosis: Techniques, Trends, and Future Directions [J].

Habchi, Yassine ;

Himeur, Yassine ;

Kheddar, Hamza ;

Boukabou, Abdelkrim ;

Atalla, Shadi ;

Chouchane, Ammar ;

Ouamane, Abdelmalik ;

Mansoor, Wathiq .

SYSTEMS, 2023, 11 (10)

[25] Application of artificial intelligence (AI) to control COVID-19 pandemic: Current status and future prospects [J].

Ashique, Sumel ;

Mishra, Neeraj ;

Mohanto, Sourav ;

Garg, Ashish ;

Taghizadeh-Hesary, Farzad ;

Gowda, B. H. Jaswanth ;

Chellappan, Dinesh Kumar .

HELIYON, 2024, 10 (04)

[26] COVID-19: Implications, Reactions and Future Directions [J].

Dhanani, Rahim ;

Wasif, Muhammad ;

Pasha, Hamdan Ahmed ;

Hussain, Muntazir ;

Ghaloo, Shayan Khalid ;

Vardag, Abdul Basit Shah ;

Mahmood, Khadija ;

Hussain, Raza .

TURKISH ARCHIVES OF OTORHINOLARYNGOLOGY, 2020, 58 (02) :122-126

[27] AI & COVID-19 [J].

Bacciu, Davide ;

Girardi, Emanuela ;

Maratea, Marco ;

Sousa, Jose .

INTELLIGENZA ARTIFICIALE, 2021, 15 (02) :45-53

[28] The impact of COVID-19 on supply chains: systematic review and future research directions [J].

Hassan Younis ;

Malek Alsharairi ;

Hammad Younes ;

Balan Sundarakani .

Operational Research, 2023, 23

[29] The impact of COVID-19 on supply chains: systematic review and future research directions [J].

Younis, Hassan ;

Alsharairi, Malek ;

Younes, Hammad ;

Sundarakani, Balan .

OPERATIONAL RESEARCH, 2023, 23 (03)

[30] Impact of COVID-19 on supply chains: lessons learned and future research directions [J].

Gupta, Rohit ;

Rathore, Bhawana ;

Biswas, Baidyanath .

INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT, 2022, 39 (10) :2400-2423

← 1 2 3 4 5 →