Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach

AI and Big Data in the COVID-19 Response

Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach is an edited collection focused on one urgent question: how data-driven methods could help researchers and healthcare workers respond to the pandemic. The volume draws together chapters on forecasting, visualization, diagnosis, prediction, and deep learning, giving the book a practical, research-forward structure rather than a single narrow theme.

Because the chapters are organized around four clear parts, the book reads as a map of early COVID-19 analytics work. Some contributions address outbreak trends and forecasting models; others look at chest imaging, prediction pipelines, and AI-based detection approaches. The result is a broad view of how artificial intelligence and big data methods were being adapted for pandemic analysis across health, imaging, and decision-support contexts.

What the Book Covers

• Forecasting and visualization of COVID-19 data
• Diagnosis and prediction using medical imaging and analytical models
• Artificial intelligence approaches to slowing the spread of the virus
• Deep learning methods applied to COVID-19 problems

A Research Collection for Technical Readers

This is a specialist edited volume for readers who want to follow the research conversation around COVID-19, machine learning, and big data analytics. It will be most useful to researchers, postgraduate students, and practitioners interested in computational approaches to public-health problems, especially where AI, forecasting, and medical-image analysis overlap.

Series Context

The book appears in Springer’s Studies in Big Data series, which is known for fast-moving work in data analytics, computational intelligence, and applied AI. That context fits the book well: it is a contemporary research snapshot, built around technical chapters and cross-disciplinary applications.

If your library or collection focuses on data science, AI for healthcare, or pandemic-era research, this title sits comfortably in that intersection.