Deep Learning and Edge Computing Solutions for High Performance Computing (Paperback, 1st ed. 2021)


This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.

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Product Description

This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.

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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

EAI/Springer Innovations in Communication and Computing

Release date

2022

Availability

Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.

First published

2021

Editors

,

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

279

Edition

1st ed. 2021

ISBN-13

978-3-03-060267-3

Barcode

9783030602673

Categories

LSN

3-03-060267-2



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