Artificial Intelligence for COVID-19

This book offers a comprehensive look at artificial intelligence applications during the COVID-19 pandemic, exploring various fields and methodologies.

In Artificial Intelligence for COVID-19, the author delves into the multifaceted applications of artificial intelligence in addressing challenges posed by the pandemic. The book covers a wide array of topics including machine learning, deep learning, advanced image processing, and computational intelligence. Each chapter is meticulously crafted to highlight how these technologies can be leveraged not only in healthcare but also in various sectors impacted by COVID-19. The integration of IoT, robotics, and automation is discussed in detail, showcasing innovative solutions that emerged during this global crisis.

The text further explores optimization techniques, mathematical modeling, and the role of neural networks in analyzing large datasets. With a focus on practical applications, the book presents recent case studies and project proposals that serve as valuable resources for postgraduate courses. Readers will find insights into how big data, data processing, and data mining can be utilized to tackle the complexities introduced by the pandemic.

Intended for researchers, decision-makers, and practitioners, Artificial Intelligence for COVID-19 serves as a comprehensive guide to understanding the intersection of AI and public health. The author's aim is to provide a thorough overview of methodologies and theoretical frameworks, ultimately contributing to the ongoing discourse on how technology can effectively respond to emerging global challenges.