Privacy-Preserving Techniques with e-Healthcare Applications

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Éditeur :

Springer


Collection :

Wireless Networks

Paru le : 2024-12-13

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Description

This book investigates novel accurate and efficient privacy-preserving techniques and their applications in e-Healthcare services. The authors first provide an overview and a general architecture of e-Healthcare and delve into discussions on various applications within the e-Healthcare domain. Simultaneously, they analyze the privacy challenges in e-Healthcare services. Then, in Chapter 2, the authors give a comprehensive review of privacy-preserving and machine learning techniques applied in their proposed solutions. Specifically, Chapter 3 presents an efficient and privacy-preserving similar patient query scheme over high-dimensional and non-aligned genomic data; Chapter 4 and Chapter 5 respectively propose an accurate and privacy-preserving similar image retrieval scheme and medical pre-diagnosis scheme over dimension-related medical images and single-label medical records; Chapter 6 presents an efficient and privacy-preserving multi-disease simultaneous diagnosis scheme over medical records with multiple labels. Finally, the authors conclude the monograph and discuss future research directions of privacy-preserving e-Healthcare services in Chapter 7.
Pages
174 pages
Collection
Wireless Networks
Parution
2024-12-13
Marque
Springer
EAN papier
9783031769214
EAN PDF
9783031769221

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
8776 Ko
Prix
137,14 €
EAN EPUB
9783031769221

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
24986 Ko
Prix
137,14 €