Introduction to the Special Track on Artificial Intelligence and COVID-19

被引:0
|
作者
Michalowski M. [1 ]
Moskovitch R. [2 ]
Chawla N.V. [3 ]
机构
[1] University of Minnesota, Minneapolis, MN
[2] Ben-Gurion University of the Negev, Beersheba
[3] University of Notre Dame, Notre Dame, IN
关键词
All Open Access; Bronze;
D O I
10.1613/JAIR.1.14552
中图分类号
学科分类号
摘要
The human race is facing one of the most meaningful public health emergencies in the modern era caused by the COVID-19 pandemic. This pandemic introduced various challenges, from lock-downs with significant economic costs to fundamentally altering the way of life for many people around the world. The battle to understand and control the virus is still at its early stages yet meaningful insights have already been made. The uncertainty of why some patients are infected and experience severe symptoms, while others are infected but asymptomatic, and others are not infected at all, makes managing this pandemic very challenging. Furthermore, the development of treatments and vaccines relies on knowledge generated from an ever evolving and expanding information space. Given the availability of digital data in the modern era, artificial intelligence (AI) is a meaningful tool for addressing the various challenges introduced by this unexpected pandemic. Some of the challenges include: outbreak prediction, risk modeling including infection and symptom development, testing strategy optimization, drug development, treatment repurposing, vaccine development, and others. © 2023 AI Access Foundation. All rights reserved.
引用
收藏
页码:523 / 525
页数:2
相关论文
共 50 条
  • [11] The prospective of Artificial Intelligence in COVID-19 Pandemic
    Swati Swayamsiddha
    Kumar Prashant
    Devansh Shaw
    Chandana Mohanty
    [J]. Health and Technology, 2021, 11 : 1311 - 1320
  • [12] Artificial intelligence for COVID-19 spread modeling
    Krivorotko, Olga
    Kabanikhin, Sergey
    [J]. JOURNAL OF INVERSE AND ILL-POSED PROBLEMS, 2024, 32 (02): : 297 - 332
  • [13] Current applications of artificial intelligence for COVID-19
    Jakhar, Deepak
    Kaur, Ishmeet
    [J]. DERMATOLOGIC THERAPY, 2020, 33 (04)
  • [14] Survey of Artificial Intelligence in COVID-19 Pandemic
    Sun, Shukui
    Fan, Jing
    Li, Zhanwen
    Qu, Jinshuai
    Lu, Peidong
    [J]. Computer Engineering and Applications, 2024, 59 (05) : 28 - 39
  • [15] Artificial Intelligence for COVID-19: Rapid Review
    Chen, Jiayang
    See, Kay Choong
    [J]. JOURNAL OF MEDICAL INTERNET RESEARCH, 2020, 22 (10)
  • [16] The 2021 COVID-19 Artificial Intelligence Issue
    Hsieh, James J.
    [J]. CLINICAL GENITOURINARY CANCER, 2021, 19 (01) : 1 - 2
  • [17] COVID-19 and Artificial Intelligence: the pandemic pacifier
    Banerjee, Indrajit
    Robinson, Jared
    Kashyap, Abhishek
    Mohabeer, Poornasha
    Sathian, Brijesh
    [J]. NEPAL JOURNAL OF EPIDEMIOLOGY, 2020, 10 (04): : 919 - 922
  • [18] Artificial intelligence and COVID-19: A multidisciplinary approach
    Ahuja, Abhimanyu S.
    Reddy, Vineet Pasam
    Marques, Oge
    [J]. INTEGRATIVE MEDICINE RESEARCH, 2020, 9 (03)
  • [19] The prospective of Artificial Intelligence in COVID-19 Pandemic
    Swayamsiddha, Swati
    Prashant, Kumar
    Shaw, Devansh
    Mohanty, Chandana
    [J]. HEALTH AND TECHNOLOGY, 2021, 11 (06) : 1311 - 1320
  • [20] Role of Artificial Intelligence in COVID-19 Detection
    Gudigar, Anjan
    Raghavendra, U.
    Nayak, Sneha
    Ooi, Chui Ping
    Chan, Wai Yee
    Gangavarapu, Mokshagna Rohit
    Dharmik, Chinmay
    Samanth, Jyothi
    Kadri, Nahrizul Adib
    Hasikin, Khairunnisa
    Barua, Prabal Datta
    Chakraborty, Subrata
    Ciaccio, Edward J.
    Acharya, U. Rajendra
    [J]. SENSORS, 2021, 21 (23)