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

by Mohammad Sufian Badar (Editor), Nima Rezaei (Editor), Hassan Imtiyaz (Editor), Jawed Ahmed (Editor), Afshar Alam PhD (Editor)

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.

• 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