Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques
  • Author : Mohammad Sufian Badar
  • Release Date : 01 May 2023
  • Publisher : Academic Press
  • Genre : Science
  • Pages : 0
  • ISBN 13 : 0323953743
  • Total Download : 525
  • File Size : 54,5 Mb

Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques PDF Summary

Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-based Techniques offers insight and demonstrates how machine learning (ML), artificial intelligence (AI), and (Internet of Things (IoT) can be used to diagnose and fight COVID-19 infection. The book in the molecular basis of pathogenesis, epidemiology, Transmission Mechanism, Diagnostic approaches, Mutational landscape of SARS-CoV-2. It also describes also discusses the challenges that we face in using these technologies. Organized into three parts, Part A covers the pathogenesis, transmission, diagnosis, and treatment strategies for COVID-19. Part B is an introduction to Artificial Intelligence and Machine Learning. This section examines machine Learning and other emerging technologies that can be used to diagnosis and treatment, but it also considers the challenges of using these technologies. Part C delves into Blockchain /IoT Blockchain technology. It examines 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. Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-based Techniques is a multidisciplinary resource for those engaged in researching COVID-19 and in how emerging technologies are being used as tools for detection, transmission, and treatment strategies.

Cyber Physical Systems

Cyber Physical Systems

Author : Ramesh Poonia,Basant Agarwal,Sandeep Kumar,Mohammad Khan,Goncalo Marques,Janmenjoy Nayak
Publisher : Academic Press
Total Download : 352
File Size : 55,8 Mb
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