Coronavirus disease 2019 (COVID-19), was initially detected in Wuhan, China in 2019, and is caused by a novel RNA virus belonging to the Coronaviridae family. For most patients who have died of COVID-19, the ultimate cause of death was pneumonia. Severe pneumonia often requires lengthy hospital stays in intensive care units and assistance breathing with ventilators-medical devices now in high demand. To quickly detect pneumonia-and therefore better distinguish between COVID-19 patients likely to need more supportive care in hospitals and those who could be followed closely at home, a number of radiologists and physicians at leading medical centres world-wide are now using artificial intelligence (AI) to augment lung imaging analysis. 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 first section details aspects of the early assessment of lung functions in coronavirus patients. The second section relates to the incorporation of AI and Machine Learning paradigms. Referencing a wealth of data that has been collected on COVID-19 particularly from an imaging standpoint, 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.
