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Privacy-Preserving Techniques with e-Healthcare Applications.
・ISBN 978-3-031-76924-5 paper EUR 129.99
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| 著者・編者 | Zhu, Dan / Feng, Dengguo / Shen, Xuemin (Sherman), |
|---|---|
| シリーズ | (Wireless Networks) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2025 |
| ページ数 | 174 pp. |
| 言語 | ENG |
| ニュース番号 | <A05-64770> |
解説
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.