COVID-19: Prediction, Decision-Making, and its Impacts

This book outlines artificial intelligence for COVID-19 issues that are ranging from prediction to decision-making for healthcare support in human lives. Starting with major COVID-19 issues and challenges, it takes possible AI-based solutions for multiple problems, such as early prediction, its role for public health, detection of positive cases, drug analysis, and healthcare support. It mainly employs publicly available data (population) to predict who should be tested for COVID-19, for example, radiological image data to detect COVID-19 positive cases from other similar and/or different manifestations, such as pneumonia, distributed healthcare support, and supply chains in the middle of COVID-19 pandemic. The book includes recently developed AI-driven tools and techniques, such as pattern recognition, anomaly detection, machine learning, and data analytics. It covers a wide range of audience from computer science and engineering to healthcare professionals.