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

$10.00
Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques (Developments in Applied Microbiology and Biotechnology)
Full access account to all ebooks! Click for details.

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

$10.00

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
Year:
2024
Pages:
402
Language:
English
Format:
PDF
Size:
17 MB
ASIN:
B0D9RWS3ZM
ISBN-10:
0323953743, 0323953735
ISBN-13:
9780323953740, 978-0323953740, 978-0-323-95374-0, 9780323953733, 978-0323953733