Literature DB >> 34976554

AI Techniques for COVID-19.

Adedoyin Ahmed Hussain1,2, Ouns Bouachir3,4, Fadi Al-Turjman2, Moayad Aloqaily5.   

Abstract

Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the existing AI techniques in clinical data analysis, including neural systems, classical SVM, and edge significant learning. Also, an emphasis has been made on regions that utilize AI-oriented cloud computing in combating various similar viruses to COVID-19. This survey study is an attempt to benefit medical practitioners and medical researchers in overpowering their faced difficulties while handling COVID-19 big data. The investigated techniques put forth advances in medical data analysis with an exactness of up to 90%. We further end up with a detailed discussion about how AI implementation can be a huge advantage in combating various similar viruses. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.

Entities:  

Keywords:  Big data; artificial intelligence; cloud computing; deep learning; the IoT

Year:  2020        PMID: 34976554      PMCID: PMC8545328          DOI: 10.1109/ACCESS.2020.3007939

Source DB:  PubMed          Journal:  IEEE Access        ISSN: 2169-3536            Impact factor:   3.367


  76 in total

1.  Automatic lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy in chest CTs.

Authors:  Yu Gu; Xiaoqi Lu; Lidong Yang; Baohua Zhang; Dahua Yu; Ying Zhao; Lixin Gao; Liang Wu; Tao Zhou
Journal:  Comput Biol Med       Date:  2018-10-12       Impact factor: 4.589

Review 2.  Artificial intelligence and medical imaging 2018: French Radiology Community white paper.

Authors: 
Journal:  Diagn Interv Imaging       Date:  2018-11-22       Impact factor: 4.026

3.  Computer-aided detection of breast cancer on mammograms: a swarm intelligence optimized wavelet neural network approach.

Authors:  J Dheeba; N Albert Singh; S Tamil Selvi
Journal:  J Biomed Inform       Date:  2014-02-06       Impact factor: 6.317

4.  Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

Authors:  Varun Gulshan; Lily Peng; Marc Coram; Martin C Stumpe; Derek Wu; Arunachalam Narayanaswamy; Subhashini Venugopalan; Kasumi Widner; Tom Madams; Jorge Cuadros; Ramasamy Kim; Rajiv Raman; Philip C Nelson; Jessica L Mega; Dale R Webster
Journal:  JAMA       Date:  2016-12-13       Impact factor: 56.272

5.  Review of the Clinical Characteristics of Coronavirus Disease 2019 (COVID-19).

Authors:  Fang Jiang; Liehua Deng; Liangqing Zhang; Yin Cai; Chi Wai Cheung; Zhengyuan Xia
Journal:  J Gen Intern Med       Date:  2020-03-04       Impact factor: 5.128

6.  CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV).

Authors:  Michael Chung; Adam Bernheim; Xueyan Mei; Ning Zhang; Mingqian Huang; Xianjun Zeng; Jiufa Cui; Wenjian Xu; Yang Yang; Zahi A Fayad; Adam Jacobi; Kunwei Li; Shaolin Li; Hong Shan
Journal:  Radiology       Date:  2020-02-04       Impact factor: 11.105

7.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

Authors:  Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng
Journal:  N Engl J Med       Date:  2020-01-29       Impact factor: 176.079

8.  A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster.

Authors:  Jasper Fuk-Woo Chan; Shuofeng Yuan; Kin-Hang Kok; Kelvin Kai-Wang To; Hin Chu; Jin Yang; Fanfan Xing; Jieling Liu; Cyril Chik-Yan Yip; Rosana Wing-Shan Poon; Hoi-Wah Tsoi; Simon Kam-Fai Lo; Kwok-Hung Chan; Vincent Kwok-Man Poon; Wan-Mui Chan; Jonathan Daniel Ip; Jian-Piao Cai; Vincent Chi-Chung Cheng; Honglin Chen; Christopher Kim-Ming Hui; Kwok-Yung Yuen
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

9.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105

10.  Precautionary measures needed for ophthalmologists during pandemic of the coronavirus disease 2019 (COVID-19).

Authors:  Kelvin H Wan; Suber S Huang; Alvin L Young; Dennis Shun Chiu Lam
Journal:  Acta Ophthalmol       Date:  2020-05       Impact factor: 3.761

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  18 in total

Review 1.  Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review.

Authors:  Carmela Comito; Clara Pizzuti
Journal:  Artif Intell Med       Date:  2022-03-28       Impact factor: 7.011

2.  ANFIS for prediction of epidemic peak and infected cases for COVID-19 in India.

Authors:  Rajagopal Kumar; Fadi Al-Turjman; L N B Srinivas; M Braveen; Jothilakshmi Ramakrishnan
Journal:  Neural Comput Appl       Date:  2021-09-21       Impact factor: 5.102

3.  Suggesting a framework for preparedness against the pandemic outbreak based on medical informatics solutions: a thematic analysis.

Authors:  Marsa Gholamzadeh; Hamidreza Abtahi; Reza Safdari
Journal:  Int J Health Plann Manage       Date:  2021-01-27

4.  A Novel Ensemble-based Classifier for Detecting the COVID-19 Disease for Infected Patients.

Authors:  Prabh Deep Singh; Rajbir Kaur; Kiran Deep Singh; Gaurav Dhiman
Journal:  Inf Syst Front       Date:  2021-04-25       Impact factor: 6.191

Review 5.  COVID-19 in the Age of Artificial Intelligence: A Comprehensive Review.

Authors:  Jawad Rasheed; Akhtar Jamil; Alaa Ali Hameed; Fadi Al-Turjman; Ahmad Rasheed
Journal:  Interdiscip Sci       Date:  2021-04-22       Impact factor: 3.492

6.  Time series forecasting of COVID-19 transmission in Asia Pacific countries using deep neural networks.

Authors:  Hafiz Tayyab Rauf; M Ikram Ullah Lali; Muhammad Attique Khan; Seifedine Kadry; Hanan Alolaiyan; Abdul Razaq; Rizwana Irfan
Journal:  Pers Ubiquitous Comput       Date:  2021-01-10

7.  The role of contemporary digital tools and technologies in COVID-19 crisis: An exploratory analysis.

Authors:  Malliga Subramanian; Kogilavani Shanmuga Vadivel; Wesam Atef Hatamleh; Abeer Ali Alnuaim; Mohamed Abdelhady; Sathishkumar V E
Journal:  Expert Syst       Date:  2021-10-06       Impact factor: 2.812

8.  Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey.

Authors:  Dinh C Nguyen; Ming Ding; Pubudu N Pathirana; Aruna Seneviratne
Journal:  IEEE Access       Date:  2021-06-30       Impact factor: 3.367

9.  Internet of Things Concept in the Context of the COVID-19 Pandemic: A Multi-Sensor Application Design.

Authors:  Alexandru Lavric; Adrian I Petrariu; Partemie-Marian Mutescu; Eugen Coca; Valentin Popa
Journal:  Sensors (Basel)       Date:  2022-01-10       Impact factor: 3.576

10.  A systematic approach for COVID-19 predictions and parameter estimation.

Authors:  Vishal Srivastava; Smriti Srivastava; Gopal Chaudhary; Fadi Al-Turjman
Journal:  Pers Ubiquitous Comput       Date:  2020-11-06
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