LEADER 03852nam 22006255 450 001 9910917788503321 005 20241213115313.0 010 $a9783031769221 010 $a3031769228 024 7 $a10.1007/978-3-031-76922-1 035 $a(MiAaPQ)EBC31837051 035 $a(Au-PeEL)EBL31837051 035 $a(CKB)37018346200041 035 $a(DE-He213)978-3-031-76922-1 035 $a(OCoLC)1482824592 035 $a(EXLCZ)9937018346200041 100 $a20241213d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPrivacy-Preserving Techniques with e-Healthcare Applications /$fby Dan Zhu, Dengguo Feng, Xuemin (Sherman) Shen 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (184 pages) 225 1 $aWireless Networks,$x2366-1445 311 08$a9783031769214 311 08$a303176921X 327 $aIntroduction -- 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. 330 $aThis book investigates novel accurate and efficient privacy-preserving techniques and their applications in e-Healthcare services. The authors first provide an overview and a general architecture of e-Healthcare and delve into discussions on various applications within the e-Healthcare domain. Simultaneously, they analyze the privacy challenges in e-Healthcare services. Then, in Chapter 2, the authors give a comprehensive review of privacy-preserving and machine learning techniques applied in their proposed solutions. Specifically, Chapter 3 presents an efficient and privacy-preserving similar patient query scheme over high-dimensional and non-aligned genomic data; Chapter 4 and Chapter 5 respectively propose an accurate and privacy-preserving similar image retrieval scheme and medical pre-diagnosis scheme over dimension-related medical images and single-label medical records; Chapter 6 presents an efficient and privacy-preserving multi-disease simultaneous diagnosis scheme over medical records with multiple labels. Finally, the authors conclude the monograph and discuss future research directions of privacy-preserving e-Healthcare services in Chapter 7. Studies the issues and challenges of privacy-preserving techniques applied in e-Healthcare services; Focuses on common and distinctive medical data, investigating accurate e-Healthcare services with privacy preservation; Proposes solutions with proof-of-concept prototypes, tested on real and simulated datasets. 410 0$aWireless Networks,$x2366-1445 606 $aTelecommunication 606 $aMedical informatics 606 $aComputational intelligence 606 $aCommunications Engineering, Networks 606 $aHealth Informatics 606 $aComputational Intelligence 615 0$aTelecommunication. 615 0$aMedical informatics. 615 0$aComputational intelligence. 615 14$aCommunications Engineering, Networks. 615 24$aHealth Informatics. 615 24$aComputational Intelligence. 676 $a621.382 700 $aZhu$b Dan$0855588 701 $aFeng$b Dengguo$0997280 701 $aShen$b Xuemin (Sherman)$0720658 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910917788503321 996 $aPrivacy-Preserving Techniques with e-Healthcare Applications$94303710 997 $aUNINA