Diagnosis and Analysis of Covid-19 Using Artificial Intelligence and Machine Learning-based Techniques. Questo articolo non è disponibile.Diagnosis and Analysis of Covid-19 Using Artificial Intelligence and Machine Learning-based Techniques

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.

Mohammad Sufian Badar, PhD, is a Professor (temporary) in the Department of Computer Science and Engineering, SEST, Jamia Hamdard, New Delhi, India. Previously, he was Senior Teaching Faculty at UC Riverside, CA, United States, and an Analytics Architect at CenturyLink in Denver, CO, United States. He holds an MS in Molecular Science and Nanotechnology and a PhD in Engineering from Lusiana Tech University. Before that, he earned an MSc. in Bioinformatics from Jamia Millia Islamia, New Delhi. With over 18 years of teaching, research, and industry experience, Dr. Sufian has published in conferences and journals, authored chapters on AI, ML, Blockchain, IoT, Computational Biology, and has six books with Elsevier, Springer, and Bentham. His area of interest is in AI, ML, Computational Biology, and the integration of AI/ML with Health Sciences.

Nima Rezaei, MD, PhD, is Professor of Clinical Immunology and Allergy at Tehran University of Medical Sciences, where he also serves as Associate Dean of International Affairs for the School of Medicine and Director of the Global Academic Program. He is Deputy President of the Research Center for Immunodeficiencies and holds an affiliated research appointment in the Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet, Sweden. He earned his MD from Tehran University of Medical Sciences and his PhD in Clinical Immunology and Human Genetics from the University of Sheffield, United Kingdom. His research addresses primary immunodeficiencies and translational immunology, with recent work extending into computational and AI-based approaches to immune profiling. He is the founder and President of the Universal Scientific Education and Research Network (USERN) and serves as co-editor of the Springer Nature series Advances in Experimental Medicine and Biology.