Springer - Computerized Systems for COVID-19 Diagnosis

This professional resource from Springer explores the integration of signal and image processing technologies to improve COVID-19 diagnosis and treatment. The text provides a deep look into how artificial intelligence and machine learning techniques support medical professionals in high-stakes environments. Readers will find detailed information on two primary applications: achieving high precision and speed in critical diagnosis, and managing the treatment of symptoms that impact the cardiovascular and neurological systems. By examining technical approaches such as deep learning, transfer learning, and transformers, this book offers a comprehensive view of modern medical technology applications. Whether you are studying time series analysis, image segmentation, or detection and classification methods, this volume serves as a technical guide for understanding the intersection of computer science and healthcare during the pandemic.