Artificial Intelligence Strategies for Analyzing COVID-19 Pneumonia Lung Imaging: Engineering and Clinical Approaches (Volume 2)

This comprehensive reference work details the latest research and developments in the utilization of AI strategies in the diagnosis and treatment of COVID-19 patients. It explores aspects of the early assessment of lung functions in coronavirus patients, as well as the incorporation of AI and Machine Learning paradigms. The text also reflects on the clinical implications of AI in COVID-19 and addresses miscellaneous topics related to the complexities and challenges of COVID-19 therapeutics. This is an essential text for academics, clinicians, and scientists working in the domain of lung cancer, data-mining, machine learning, and deep learning within the COVID-19 environment. Key Features: Comprehensive overview of the implementation of artificial intelligence (AI) and machine learning (ML) strategies to the diagnosis, follow on/follow-up, and treatments of COVID-19 patients. A number of authors and contributors are front-line researchers and clinicians in COVID-19 patient affairs from around the world. Provides unique coverage of AI and Machine Learning in the prediction of bloodclotting in COVID-19 patients. Offers specific examples of diagnosing COVID-19 with AI utilization within CT. Presents extensive references at the end of each chapter to enhance further study.