£123.63

Springer - Computerized Systems for COVID-19 Diagnosis

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Description

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.

Key Features

Covers the application of artificial intelligence and machine learning to support the diagnosis and treatment of COVID-19.

Focuses on critical diagnosis methods that require high speed and precision for patient care.

Explores treatment strategies for symptoms affecting the cardiovascular and neurological systems.

Includes technical discussions on signal processing, time series analysis, and image segmentation.

Details advanced methodologies including deep learning, transfer learning, and transformers for detection and classification.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
28 June 2024
Listed Since
29 June 2024

Barcode

No barcode data available

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