Privacy-Preserving Techniques with e-Healthcare Applications / / by Dan Zhu, Dengguo Feng, Xuemin (Sherman) Shen

• Autore: Zhu Dan
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
• Edizione: 1st ed. 2024.
• Descrizione fisica: 1 online resource (184 pages)
• Disciplina: 621.382
• Soggetto topico: Telecommunication; Medical informatics; Computational intelligence; Communications Engineering, Networks; Health Informatics; Computational Intelligence
• Altri autori: FengDengguo ShenXuemin (Sherman)
• Nota di contenuto: 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.
• Sommario/riassunto: 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. 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.
• Titolo autorizzato: Privacy-Preserving Techniques with e-Healthcare Applications
• ISBN: 9783031769221; 3031769228
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910917788503321
• Lo trovi qui: Univ. Federico II
• Serie: Wireless Networks, . 2366-1445