000			04025nam a22005655i 4500
001			978-3-031-76922-1
003			DE-He213
005			20251030114616.0
007			cr nn 008mamaa
008			241213s2024 sz | s |||| 0|eng d
020			_a9783031769221 _9978-3-031-76922-1
024	7		_a10.1007/978-3-031-76922-1 _2doi
050		4	_aTK5101-5105.9
072		7	_aTJK _2bicssc
072		7	_aTEC041000 _2bisacsh
072		7	_aTJK _2thema
100	1		_aZhu, Dan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _988869
245	1	0	_aPrivacy-Preserving Techniques with e-Healthcare Applications _h[electronic resource] / _cby Dan Zhu, Dengguo Feng, Xuemin (Sherman) Shen.
250			_a1st ed. 2024.
264		1	_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2024.
300			_aXII, 174 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aWireless Networks, _x2366-1445
505	0		_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.
520			_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.
650		0	_aTelecommunication.
650		0	_aMedical informatics. _960693
650		0	_aComputational intelligence. _964052
650	1	4	_aCommunications Engineering, Networks.
650	2	4	_aHealth Informatics.
650	2	4	_aComputational Intelligence. _964052
700	1		_aFeng, Dengguo. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _988870
700	1		_aShen, Xuemin (Sherman). _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _970857
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783031769214
776	0	8	_iPrinted edition: _z9783031769238
776	0	8	_iPrinted edition: _z9783031769245
830		0	_aWireless Networks, _x2366-1445 _967497
856	4	0	_uhttps://doi.org/10.1007/978-3-031-76922-1
912			_aZDB-2-SME
912			_aZDB-2-SXM
999			_c65683 _d65683