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<br><br>
<h3 class="p-border">Welcome to the tutorial page of "AI techniques to combat COVID-19" </h3>
<p> <b>AI techniques to combat COVID-19 </b> <br>
Instructors: Sonali Agarwal, Narinder Singh Punn, Sanjay Sonbhadra<br>
The rampant outbreak of the novel coronavirus (COVID-19, SARS-Cov-2),
during early December 2019 in Wuhan, China, has created a staggering worldwide
crisis along with the widespread loss of lives. The scarcity of resources and lack
of experiences to endure the COVID-19 pandemic, combined with the fear of future
consequences has established the need for adoption of Artificial Intelligence
(AI) techniques to address the challenges. Motivated by the need to highlight
the need for employing AI in combating the COVID-19 pandemic, this tutorial
aims to help the audience to gain comprehensive understanding of the current
state of AI applications in developing the computer-assisted (controlling,
monitoring, discovery, diagnosing and treatment) systems to battle the
COVID-19 crisis along with the AI assisted spread containment measures.
<p> <b>Presenters’ detail:</b>
<p> <b>Sonali Agarwal</b><br>
Affiliation: Associate Professor, Department of IT, Indian Institute of Information Technology,
Allahabad, India<br>
Address: Room No. 5203, CC-III Building, Indian Institute of Information Technology, Allahabad,
Deoghat, Jhalwa, Prayagraj-211015, India<br>
Email: sonali@iiita.ac.in<br>
<p><b>Narinder Singh Punn</b><br>
Affiliation: Senior Research Fellow, Department of IT, Indian Institute of Information Technology,
Allahabad, India<br>
Address: Room No. 5241, CC-III Building, Indian Institute of Information Technology, Allahabad,
Deoghat, Jhalwa, Prayagraj-211015, India<br>
Email: pse2017002@iiita.ac.in<br>
<p> <b>Sanjay Kumar Sonbhadra </b><br>
Affiliation: Senior Research Fellow, Department of IT, Indian Institute of Information Technology,
Allahabad, India<br>
Address: Room No. 5241, CC-III Building, Indian Institute of Information Technology, Allahabad,
Deoghat, Jhalwa, Prayagraj-211015, India<br>
Email: rsi2017502@iiita.ac.in<br>
<p> <b>Biographical sketch:</b><br>
<p><b> Sonali Agarwal (SA) </b><br>
Dr. Sonali Agarwal is working as an Associate Professor in the Information Technology Department of
Indian Institute of Information Technology (IIIT), Allahabad, India. She received her Ph. D. Degree at IIIT
Allahabad and joined as faculty at IIIT Allahabad, where she has been teaching since October 2009. She
holds Bachelor of Engineering (B.E.) degree in Electrical Engineering from Bhilai Institute of Technology,
Bhilai, (C.G.) India and Masters of Engineering (M.E.) degree in Computer Science from Motilal Nehru
National Institute of Technology (MNNIT), Allahabad, India Her main research interests are in the areas
of Artificial Intelligence and Big Data. She is the head of Big Data Analytics Lab at IIIT Allahabad, India.
<p> <b>Narinder Singh Punn (NSP)</b> <br>
Mr. Narinder Singh Punn is working as Senior Research Fellow in the Information Technology
Department of Indian Institute of Information Technology (IIIT), Allahabad, India. Narinder’s main
research includes Medical Imaging segmentation, Deep learning and Artificial Intelligence techniques in
healthcare. He is a senior member of Big Data Analytics Lab at IIIT Allahabad, India. His recent
publications cover applications of deep learning in detection and prevention of COVID-19.
<p> <b>Sanjay Kumar Sonbhadra (SKS) </b> <br>
Mr. Sanjay Kumar Sonbhadra is working as Senior Research Fellow in the Information Technology
Department of Indian Institute of Information Technology (IIIT), Allahabad, India. He is mainly working on
One Class Classification, Anomaly detection, Dimensionality reduction techniques for target specific
mining. He is a senior member of Big Data Analytics Lab at IIIT Allahabad, India. Sanjay has published
many articles in the area of machine learning applications to address recent challenges of COVID-19.
<p><b>Objectives:</b>
<br>The objectives of this tutorial are highlighted below:
<ul>
<li> Building awareness about the current advancements in AI to combat COVID-19 pandemic.</li>
<li> Highlighting the tools, techniques, and applications from the perspective of future intensive
applications.</li>
<li> Providing a platform to participants for one-to-one interaction.</li></ul>
<p> <b>Tutorial outline:</b>
<br>The outline of the tutorial is described below:
<p><b>Part 1 - Introduction </b>
<br>This section describes the overview of COVID-19 pandemic and how artificial intelligence can drive the battle against COVID-19
<ul>
<li>Overview of COVID-19 [6]</li>
<li>Overview of artificial intelligence[7]</li>
<li>AI Vs non-AI based applications to combat COVID-19 [8]. </li></ul>
<p><b>Part 2 - Fundamentals of machine learning and deep learning</b>
<br>In this section various fundamentals and building blocks of the machine learning and deep learning models are discussed concerning the state-of-the-art developments.
<ul>
<li>Building blocks and fundamentals of:</li>
<ul>
<li> Machine learning</li>
<li> Deep learning and Computer vision</li>
<li> Data Science</li>
</ul>
</ul>
<p> <b>Part 3 - Main applications of AI in COVID-19 pandemic - I </b>
<br>With AI being playing a vital role to combat COVID-19 pandemic, this section discusses the tasks such as detection, prevention, response and recovery to provide smart computer-assisted
systems.
<ul>
<li>Detection: early warning, diagnosis and prognosis [1,2]</li>
<li> Prevention: prediction, surveillance, information in treatment and drug discovery [3]</li>
<li> Response: Delivery and service automation: telemedicine and assistance on demand [4]</li>
<li> Recovery: Monitoring and controlling [5]</li>
</ul>
<p><b>Part 4 - Main applications of AI in COVID-19 pandemic - II</b>
<br>Following from the AI advancements this section elaborates on the approaches to trace, track and forecast the nature of virus using the available data sources.
<ul>
<li> Projection of cases, mortality and propagation analysis [6, 9]
<li>Spread containment [10, 11]</li>
<li>Fighting “infodemic” [12, 13]</li>
</ul>
<p><b>Part 5 - Main applications of AI in COVID-19 pandemic - III</b>
<br>In this section post-COVID-19 analysis is conducted from the perspective of AI approaches while presenting the various measures undertaken to control the spread and prevent future pandemic
crises.
<ul>
<li>Preparedness to economic disruption [14, 15]</li>
<li> Social Control (contact less initiatives) [16, 17]</li>
<li> COVID-19 information retrieval [18]</li>
<li> Prevention of the disease [19]</li>
</ul>
<p><b>Part 6 - Conclusion and Future Trends</b>
<br>This section provides the concluding remarks and possible research directions with AI technology.
<p> <b>Audience background:</b>
<br> The tutorial has no prerequisites but general knowledge about artificial intelligence (AI) is acceptable. The tutorial first gives a brief overview of COVID-19 pandemic and its worldwide impact to setup the
foundation of the research possibilities to combat COVID-19 using AI technologies. Later, the fundamentals and particularities of artificial intelligence concerned with machine learning and deep
learning are discussed, followed by many applications of AI to combat COVID-19 pandemic with the state-of-the-art approaches with the aim of benefiting the maximum number of participants. The tutorial
is on an emerging topic, which should be interesting to many researchers.
<p> <b> Audio Visual equipment needed for the presentation:</b><br>
The only requirement is a room equipped with a computer and multimedia projector
</p> <br>
<p><b>References:</b><br>
[1]. Punn, N.S., Agarwal, S. Automated diagnosis of COVID-19 with limited posteroanterior chest X-
ray images using fine-tuned deep neural networks. Appl Intell (2020).<br>
[2]. Punn, N. S. and Agarwal, S. (2020b). Chs-net: A deep learning approach for hierarchical
segmentation of covid-19 infected ct images. arXiv preprint arXiv:2012.07079.<br>
[3]. Senior, A. W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., Green, T., Qin, C., ˇZ ́ıdek, A.,
Nelson, A. W., Bridgland, A., et al. (2020). Improved protein structure prediction using potentials
from deep learning. Nature, pages 1–5.<br>
[4]. Wosik, Jedrek, Marat Fudim, Blake Cameron, Ziad F. Gellad, Alex Cho, Donna Phinney, Simon
Curtis et al. "Telehealth transformation: COVID-19 and the rise of virtual care." Journal of the
American Medical Informatics Association 27, no. 6 (2020): 957-962.<br>
[5]. Stebbing J, Phelan A, Griffin I, Tucker C, Oechsle O, Smith D, Richardson P. COVID-19:
combining antiviral and anti-inflammatory treatments. Lancet Infect Dis 2020 Feb 27.<br>
[6]. Punn, Narinder Singh, Sanjay Kumar Sonbhadra, and Sonali Agarwal. "COVID-19 epidemic
analysis using machine learning and deep learning algorithms." MedRxiv (2020).<br>
[7]. Agarwal, Sonali, Narinder Singh Punn, Sanjay Kumar Sonbhadra, P. Nagabhushan, K. K.
Pandian, and Praveer Saxena. "Unleashing the power of disruptive and emerging technologies
amid COVID 2019: a detailed review." arXiv preprint arXiv:2005.11507 (2020).<br>
[8]. Vaishya, Raju, Mohd Javaid, Ibrahim Haleem Khan, and Abid Haleem. "Artificial Intelligence (AI)
applications for COVID-19 pandemic." Diabetes & Metabolic Syndrome: Clinical Research &
Reviews 14, no. 4 (2020): 337-339.<br>
[9]. McKibbin, W. J. and Fernando, R. (2020). The global macroeconomic impacts of covid-19: Seven
scenarios.<br>
[10]. Punn, Narinder Singh, Sanjay Kumar Sonbhadra, and Sonali Agarwal. "Monitoring COVID-19
social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort
techniques." arXiv preprint arXiv:2005.01385 (2020).<br>
[11]. Chowdary, G. Jignesh, Narinder Singh Punn, Sanjay Kumar Sonbhadra, and Sonali Agarwal.
"Face mask detection using transfer learning of inceptionv3." In International Conference on Big
Data Analytics, pp. 81-90. Springer, Cham, 2020.<br>
[12]. Zarocostas, J. (2020). How to fight an infodemic. https://www.thelancet.com/action/.<br>
[13]. Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., Zola,
P., Zollo, F., and Scala, A. (2020). The covid-19 social media infodemic. arXiv preprint
arXiv:2003.05004.<br>
[14]. Conerly, B. (2020). Rolling recessions are the likely economic impact of new coronavirus and
covid-19. https://www.forbes.com/sites/billconerly/<br>
[15]. Sood, R. (2020). The trends shaping the post-covid-19 world.<br>
https://www.thehindu.com/opinion/lead/the-trends-shaping-the-post-covid-19-
world/article31552150.ece.<br>
[16]. Yancey-Bragg (2020). Going to a drive-thru covid-19 testing site? here’s a step-by-step look at
what to expect.<br>
https://www.usatoday.com/story/news/health/2020/03/20/drive-thru-coronavirus-testing-step-
step-look-what-expect/2873324001/<br>
[17]. Wosik, J., Fudim, M., Cameron, B., Gellad, Z. F., Cho, A., Phinney, D., Curtis, S., Roman, M.,
Poon, E. G., Ferranti, J., et al. (2020). Telehealth transformation: Covid-19 and the rise of virtual
care. Journal of the American Medical Informatics Association.<br>
[18]. Sonbhadra, Sanjay Kumar, Sonali Agarwal, and P. Nagabhushan. "Target specific mining of
COVID-19 scholarly articles using one-class approach." Chaos, Solitons & Fractals 140 (2020):
110155.<br>
[19]. Fragkou, Paraskevi C., Drifa Belhadi, Nathan Peiffer-Smadja, Charalampos D. Moschopoulos,
François-Xavier Lescure, Hannah Janocha, Emmanouil Karofylakis et al. "Review of trials
currently testing treatment and prevention of COVID-19." Clinical Microbiology and Infection
(2020).<br>
[20]. Sonali Agarwal (2021). Tutorial on AI techniques to combat COVID-19.
https//:profile.iiita.ac.in/sonali/tutorials.html<br>
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<span class="w3-opacity w3-large p-border">CONTACT</span><br>
Dr. Sonali Agarwal <br>
Associate Professor<br>
Room No.: 5203, CC3 Building <br>
Indian Institute of Information Technology - Allahabad
Devghat, Jhalwa,
Prayagraj(Allahabad) 211015, (UP) INDIA
<br>
Tel : 0532-2922424<br>
Email : sonali@iiita.ac.in<br>
Alt Email : raiagarwalsonali@gmail.com<br>
Website : www.sonaliagarwal.com<br>
Google Scholar: <a href="https://scholar.google.co.in/citations?user=hPvt6d8AAAAJ">https://scholar.google.co.in/citations?user=hPvt6d8AAAAJ</a>
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