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| Full Title | Artificial Intelligence Strategies for Analyzing COVID-19 Pneumonia Lung Imaging, Volume 1 Characterization approaches |
|---|---|
| Author(s) | Ayman El-Baz and Jasjit S Suri |
| Edition | |
| ISBN | 9780750337953, 9780750337939, 9780750337960, 9780750337946, 9780750345392 |
| Publisher | Institute of Physics Publishing |
| Format | PDF and EPUB |
The utilization of AI strategies for diagnosis, follow-up, and treatments of COVID-19 patients is now becoming essential. This is the first comprehensive reference work published detailing the latest research and developments in the utilization of AI strategies in the diagnosis and treatment of COVID-19 patients. The book references a wealth of data that has been collected on COVID-19 particularly from an imaging standpoint, with the first section detailing aspects of the early assessment of lung functions in coronavirus patients, and the second section relating to the incorporation of AI and Machine Learning paradigms. This book is important 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/contributors are front-line researchers and clinicians in COVID-19 patient affairs, representing the USA, India, UK, France and importantly China. Provides unique coverage of AI and Machine Learning in the prediction of blood-clotting 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.
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