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E-grāmata: Researches and Applications of Artificial Intelligence to Mitigate Pandemics: History, Diagnostic Tools, Epidemiology, Healthcare, and Technology

Edited by , Edited by (Assistant Professor, Department of Data Science, School of Science, Engineering and Environment, University of Sal), Edited by (Lecturer, King Faisal University, College of Computer Science, Inforamtion's System Department, Al-Ahsa, Saudi Arabia)
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Researches and Applications of Artificial Intelligence to Mitigate Pandemics: History, Diagnostic Tools, Epidemiology, Healthcare, and Technology offers readers an interdisciplinary view of state-of-art research related to the COVID-19 outbreak, with a focus on tactics employed to model the number of cases of COVID-19 (time series modeling), models employed to diagnostics COVID-19 based on images, and the panoramic of COVID-19 since its discovery and up to this book's publication. This book showcases the algorithms and models available to manage pandemic data, the role of AI, IoT and Mathematical Modeling, how to prevent and fight COVID-19, and the existing medical, social and pharmaceutical support.

Chapters cover methods and protocols, the basics and history of diseases, the fast diagnosis of disease with different automated algorithms and artificial intelligence tools and techniques, the methods of handling epidemiology for mitigating the spread of disease, artificial intelligence and mathematical modeling techniques, and how mental and physical health is affected with social media usage.

  • Explains novel and hybrid high quality artificial intelligence methodologies, techniques, algorithms, architectures, tools and methods to cope with pandemics
  • Covers rapid point-of-care diagnostics, presents details on varied mathematical models developed to control epidemiology, and lists existing measures to disseminate the spread of infection using computational methods
  • Highlights the negative effect of social media and other sources by applying preventive measures to combat depression and anxiety
Contributors ix
1 A case of 2019-nCoV novel coronavirus outbreak
1(22)
Asma Fatima
Khutaija Maheen
Kauser Hameed
1.1 Introduction
1(9)
1.1.1 History of coronavirus
3(2)
1.1.2 Novel coronavirus-2019
5(2)
1.1.3 Infectivity of COVID-19
7(1)
1.1.4 Clinical symptoms and its effect
8(2)
1.2 Necessary precautions
10(4)
1.2.1 Appropriate mask and its availability
11(1)
1.2.2 Role of disinfectants
12(1)
1.2.3 Immunity boosters
12(2)
1.3 Demystify COVID-19
14(3)
1.3.1 Suspicious symptoms
14(1)
1.3.2 Available approaches for treatment
15(1)
1.3.3 Medical observation
16(1)
1.3.4 Reinfection
16(1)
1.4 Dispelling rumors
17(2)
1.4.1 Young people and COVID-19
18(1)
1.4.2 Medicines available for curing virus
18(1)
1.5 Conclusion
19(4)
References
20(3)
2 Diagnostic tools and automated decision support systems for COVID-19
23(28)
Noor E. Hafsa
2.1 Introduction
23(1)
2.2 Molecular assay-based diagnosis
24(3)
2.2.1 Reverse transcriptase polymerase chain reaction
25(1)
2.2.2 RT-PCR assay procedure
25(1)
2.2.3 Diagnostic precision of RT-PCR-based diagnosis
25(1)
2.2.4 Limitations of RT-PCR-based diagnosis
26(1)
2.2.5 Conclusion
27(1)
2.3 Serological and immunological assay-based diagnosis
27(4)
2.3.1 Types of serology-based testing
28(1)
2.3.2 Diagnostic precision of serology-based testing
29(1)
2.3.3 Uses of laboratory-based assays in the context of Al and data science
30(1)
2.3.4 Conclusion
30(1)
2.4 Chest and lung imaging-based diagnosis
31(20)
2.4.1 Chest X-ray imaging modality
31(1)
2.4.2 COVID-19 diagnosis using chest X-ray
31(1)
2.4.3 Computer-aided diagnosis (CAD) using chest X-ray
32(5)
2.4.4 Diagnostic precision of CXR-based diagnosis
37(1)
2.4.5 Benefits and limitations of CXR-based diagnosis
37(1)
2.4.6 Chest CT-scan imaging modality
37(2)
2.4.7 COVID-19 diagnosis using chest CT scan
39(1)
2.4.8 Computer-aided diagnosis using chest CT scan
39(2)
2.4.9 Diagnostic precision of CT-based diagnosis
41(1)
2.4.10 Benefits and limitations of CT-based diagnosis
42(1)
2.4.11 Case study: radiology observations vs. CAD
42(1)
2.4.12 Lung ultrasound imaging modality
43(1)
2.4.13 COVID-19 diagnosis using lung ultrasound
43(2)
2.4.14 Conclusion
45(1)
References
45(6)
3 Epidemiology
51(28)
Khutaija Maheen
Fatima Rubeena
Kauser Hameed
3.1 Introduction
51(1)
3.2 The mathematical modeling establishment in epidemiology
52(1)
3.3 Mathematical modeling methodologies in epidemiology
53(1)
3.4 The philosophy of mathematical modeling
54(5)
3.4.1 Complexity of the model
55(1)
3.4.2 Testing of hypothesis and formulation of a model
56(3)
3.5 The nature of epidemiological data
59(2)
3.5.1 Stationary time series
60(1)
3.5.2 Autocorrelograms
61(1)
3.6 Microparasitic infections from childhood
61(1)
3.7 A simple epidemic model - COVID case studies
62(10)
3.7.1 Different models
62(1)
3.7.2 The process of transmission
62(1)
3.7.3 Between-compartment flux of individuals
63(3)
3.7.4 Dynamics analysis and deterministic setup of COVID
66(2)
3.7.5 The average age and statistics at infection
68(1)
3.7.6 Data analysis vs COVID cases
69(3)
3.8 SEIQDR model
72(3)
3.8.1 SEIR model
72(1)
3.8.2 SEIQDR model
73(2)
3.9 SEQIR model
75(1)
3.10 SEIARD model
76(1)
3.11 SIR model
77(1)
3.12 Summary
77(2)
References
78(1)
4 Social media sentiment analysis and emotional intelligence including women role during COVID-19 crisis
79(30)
Rameezunnisa
Khutaija Maheen
4.1 Introduction
79(2)
4.2 Background
81(15)
4.2.1 Importance of social media
82(1)
4.2.2 Social media versus misleading information
83(5)
4.2.3 Sentiment analysis and emotional intelligence
88(8)
4.3 Role of women during COVID-19 pandemic
96(6)
4.3.1 Women care, duties, and COVID-19
96(1)
4.3.2 Women duties during COVID-19
97(3)
4.3.3 Principle measures and principle alternatives
100(2)
4.4 Related works
102(4)
4.5 Result and discussion
106(1)
4.6 Conclusions
107(2)
References
108(1)
5 Role of technology in COVID-19 pandemic
109(1)
Raazia Saher
Madiha Anjum
5.1 Introduction
109(1)
5.2 Technology and medical science
110(1)
5.2.1 Electrocardiography (EKG)
110(1)
5.2.2 X-ray
111(1)
5.2.3 Ultrasound
111(1)
5.2.4 MRI
111(1)
5.3 Past pandemics and technology
111(2)
5.3.1 Simulation models
112(1)
5.3.2 Electronic surveillance system
112(1)
5.3.3 Monitoring online search engines
112(1)
5.4 Use of technology during COVID-19
113(22)
5.4.1 Internet of Things (IoT) and Internet of Medical Things (IoMT)
113(8)
5.4.2 Drone technology
121(4)
5.4.3 Robots
125(5)
5.4.4 Bluetooth and GPS technology
130(3)
5.4.5 Telemedicine: a new era
133(2)
5.5 Case study
135(1)
5.5.1 AAROGYA SETU app
135(1)
5.6 Conclusion
135(4)
References
136(3)
6 Conclusions
139(24)
Saneh Lata Yadav
Ritika Dhaiya
Surbhi Bhatia
6.1 Introduction
139(1)
6.2 Data science and its applications
140(4)
6.2.1 Patient prioritization to control risk
140(1)
6.2.2 Diagnosis and screening
140(1)
6.2.3 Modeling for epidemic
141(1)
6.2.4 Tracing the contacted people
141(1)
6.2.5 Acknowledging social interventions
142(1)
6.2.6 Use of case data
142(1)
6.2.7 Textual data
143(1)
6.2.8 Biomedical data
144(1)
6.2.9 Other supportive datasets
144(1)
6.2.10 Competition database
144(1)
6.3 Survey on ongoing research
144(6)
6.3.1 Image data analysis
145(1)
6.3.2 Audio data analysis
145(1)
6.3.3 Sensor data analysis
145(1)
6.3.4 Drug discovery analysis
146(4)
6.4 Bibliometric data collection
150(1)
6.5 Data science and cross cutting challenges
150(4)
6.5.1 Data confines
150(1)
6.5.2 Exactitude of output versus urgency
151(2)
6.5.3 Ethics, security, and privacy
153(1)
6.5.4 Requirement of multidisciplinary collaboration
153(1)
6.5.5 Latest data modalities
154(1)
6.5.6 Results for the developing world
154(1)
6.6 Summary
154(9)
References
155(8)
Index 163
Kauser Hameed, is a lecturer at King Faisal University College of Computer Science - Informations System department. She earned her Bachelors degree in Computer's Application from Osmania University, India in 2002 and completed her Master levels in Computers Application from the same campus in 2004. In more than a decade of her work experience, she hold promising and vivid work roles in multinational IT sectors such as GE Capitals and Sumtotal, while devoting her services in Academic later to that. Editing books, participating chapters and compiling academic videos is also one of her interesting diversions. Surbhi Bhatia Khan is Doctorate in Computer Science and Engineering in the area of Machine Learning and Social Media Analytics. She earned Project Management Professional Certification from reputed Project Management Institute, USA. She is currently working in the Department of Data Science, School of Science, Engineering and Environment, University of Salford, Manchester, United Kingdom. She has more than 11 years of academic and teaching experience in different universities. She is the awardee of the Research Excellence award given by King Faisal University, Saudi Arabia, in 2021. She has published 100ž papers in many reputed journals in high indexed outlets. She has around 12 international patents from India, Australia, and the United States. She has successfully authored 3 books and has also edited 12 books. She has completed many projects approved from Ministry of Education, Saudi Arabia, and Deanship of Scientific Research in different universities in Saudi Arabia and from India. Her area of interest is Knowledge Management, Information Systems, Machine Learning, and Data Science. Syed Tousif Ahmed holds a Masters of Computer Science and Engineering; graduated from Jawaharlal Nehru Technological University Hyderabad, India. His expertise lend strong hands on to High Performance Computing, Artificial Intelligence, Cloud database, Python, Linux administration and Data Science. Holding over 10 plus years of work experience in the field of Information Technology, he played vivid roles as working in Academics as well as in the industry. In his career journey he worked as a Database Administrator in University of Dammam, Oracle HR consultant at Extra Zonic Dammam, R and D associate at various funded research projects at renowned universities internationally and proved to show distinguished results. Currently, he is aspiring to pursue doctorate in one of his engrossing areas.
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