Privacy-Preserving Techniques with e-Healthcare Applications
Series: Wireless Networks;
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Product details:
- Edition number 2025
- Publisher Springer Nature Switzerland
- Date of Publication 14 December 2024
- Number of Volumes 1 pieces, Book
- ISBN 9783031769214
- Binding Hardback
- No. of pages174 pages
- Size 235x155 mm
- Language English
- Illustrations XII, 174 p. Illustrations, color 620
Categories
Long 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.
MoreTable of Contents:
Introduction.- An Overview of e-Healthcare.- Privacy-Preserving and Machine-Learning Techniques.- Privacy-Preserving Similar Patient Query Services over Genomic Data.- Privacy-Preserving Similarity Retrieval Services over Medical Images.- Privacy-Preserving Pre-diagnosis Services over Single-label Medical Records.- Privacy-Preserving Pre-diagnosis Services over Multi-label Medical Records.- Future Works.- Conclusion.
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