Над 4 милиона заглавия на английски и други езици! Открийте новата си история още днес! Безплатна доставка за поръчки над 69.99€

Виж статуса на поръчката

Свържете се с нас

Artificial Intelligence and Machine Learning for COVID-19

Name: Artificial Intelligence and Machine Learning for COVID-19
Brand: Springer Nature Switzerland AG
SKU: 9783030601904
Price: 130.03 EUR
Availability: InStock

Автор: Fadi Al-Turjman

Език:

Корици: С меки корици

Издател: Springer Nature Switzerland AG

Наличност: Външен склад

Изпращаме след 5-8 дни

130.03 € 254.31 лв

This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial inte...

Информация за книгата

Автор

Fadi Al-Turjman

Език

Английски език

Корици

Книга - С меки корици

Издадена

2022

страници

266

EAN

9783030601904

Enbook ID

38633804

Издател

Springer Nature Switzerland AG

Теглоt

427

Размери

155 x 235 x 16

Пълно описание

This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) - from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies.