Privacy-Preserving Techniques with e-Healthcare Applications
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Privacy-Preserving Techniques with e-Healthcare Applications

SKU: 9783031769221

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Additional information

Full Title

Privacy-Preserving Techniques with e-Healthcare Applications
Author(s)

Dan Zhu, Dengguo Feng, Xuemin (Sherman) Shen
Edition
ISBN

9783031769221, 9783031769214
Publisher

Springer
Format

PDF and EPUB

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.

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