Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques Developments in Applied Microbiology and Biotechnology Series

Langue : Anglais

Coordonnateurs : Badar Mohammad Sufian, Rezaei Nima, Imtiyaz Hassan, Ahmed Jawed, Alam Afshar

Couverture de l’ouvrage Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques

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Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques offers new insights and demonstrates how machine learning (ML), artificial intelligence (AI), and (Internet of Things (IoT) can be used to diagnose and fight COVID-19 infection. Sections also discuss the challenges we face in using these technologies. Chapters cover pathogenesis, transmission, diagnosis, and treatment strategies for COVID-19, Artificial Intelligence and Machine Learning, and Blockchain /IoT Blockchain technology, examining how AI can be applied as a tool for detection and containment of the spread of COVID-19, and on the socioeconomic and educational post-pandemic impacts of the disease. This is a multidisciplinary resource for those engaged in researching COVID-19 and how emerging technologies are being used as tools for detection, transmission and treatment strategies.

Part A: Biology of SARS-CoV-2 1. Understanding the molecular basis of pathogenesis of SARS-CoV-2 2. Epidemiology, evolution, and phylogeny of Coronaviruses 3. Transmission Mechanism and clinical manifestations of SARS-CoV-2 4. Diagnostic approaches in SARS-CoV-2 Infection (COVID-19) 5. Emerging therapeutic strategies for COVID-19 6. Vaccine development strategies and impact 7. Mutational landscape and emerging variants of SARS-CoV-2 8. Clinical management of Post COVID-19 symptoms and consequences Part B: Machine Learning 9. Introduction of Artificial Intelligence (AI) and Machine Learning (ML) 10. Emerging Technologies for Coronaviruses (COVID-19) 11. Diagnosing Coronaviruses (COVID-19) Using Machine Learning 12. Radiology Images in Machine Learning: Diagnosing and Combatting COVID-19 13. Challenges and Constraints of Using Radiology Images to Diagnose COVID-19 Part C: Blockchain / IoT 14. Artificial Intelligence (AI) and Internet of Things (IoT): Application in Detecting and Containing the Spread of Covid-19 15. Checking Covid-19 Transmission Using IoT 16. Interpretation and validation of data obtained from Artificial Intelligence 17. Socioeconomic and Educational Impact of Pandemic and Use of Blockchain to Control It

Dr. M.S Badar, MS, PhD served as a Teaching Faculty in the Department of Bioengineering at the University of California, Riverside, CA, USA. He graduated with an MS degree in Molecular Science and Nanotechnology and Ph.D. in Engineering from Louisiana Tech University Ruston, LA, USA, respectively. Dr. Badar has over 14 years of teaching, research, and industry experience. He has authored a chapter in a book about Machine Learning and Molecular Modeling. He has developed an algorithm for Face Detection, Recognition, and Emotion Recognition. He has developed a device that, by using a Biosensor, can correlate the physiology of the human body with the emotion recognition algorithm, giving us an accurate measurement of stress hormones in the body. His group is developing an ML Model which predicts Covid infection based on the severity of symptoms (mild, moderate, and severe) and if they have had contact with a Covid patient.
Professor Nima Rezaei gained his medical degree (MD) from Tehran University of Medical Sciences and subsequently obtained an MSc in Molecular and Genetic Medicine and a PhD in Clinical Immunology and Human Genetics from the University of Sheffield, UK. He also spent a short-term fellowship of Pediatric Clinical Immunology and Bone Marrow Transplantation in the Newcastle General Hospital. Professor Rezaei is now the Full Professor of Immunology and Vice Dean of Research, School of Medicine, Tehran University of Medical Sciences, and the co-founder and Head of the Research Center for Immunodeficiencies. He is also the founding President of the Universal Scientific Education and Research Network (USERN). Professor Rezaei has already been the Director of more than 55 research projects and has designed and participated in several international collaborative projects. Professor Rezaei is an editorial assistant or board member for more than 30 international journals. He has edited more than 35 international books, has presented more than 500 lectures/po

Describes the molecular basis of pathogenesis, epidemiology, transmission mechanism, diagnostic approaches, and the mutational landscape of SARS-CoV-2
Provides insights into post COVID-19 symptoms and consequences
Demonstrates how machine learning, AI, and IoT is used to diagnose and fight COVID-19 infection
Examines the use of Blockchain technology/IoT and interpretation and validation of data obtained from artificial intelligence