prof sukanya (50 risultati)

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book 'Blockchain-Enabled Federated Learning for Privacy and Security' explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. 72 pp. Englisch.

Paperback. Condizione: new. Paperback. Le livre "Blockchain-Enabled Federated Learning for Privacy and Security" explore l'integration de la technologie blockchain et de l'apprentissage federe pour relever les defis critiques du partage des donnees de sante. Avec l'essor des dossiers medicaux electroniques, de l'imagerie medicale, des appareils IoMT et de la genomique, il est devenu essentiel de proteger la vie privee des patients tout en permettant une IA collaborative. La blockchain assure la decentralisation, l'immutabilite et la confiance, tandis que l'apprentissage federe garantit l'entrainement des modeles sans exposer les donnees brutes. Ensemble, ils forment un cadre preservant la vie privee, auditable et evolutif pour l'IA dans le domaine de la sante. Le livre couvre les principes fondamentaux, les architectures de systeme, les techniques cryptographiques et les compromis de performance, ainsi que des etudes de cas reels dans la recherche sur le cancer, l'IoMT et le diagnostic COVID-19. Il met en evidence les considerations reglementaires et ethiques telles que le GDPR, l'HIPAA et le DPDP Act de l'Inde, et propose des recherches futures sur l'integration quantique, l'IA explicable, la FL equitable et la gouvernance par le biais de contrats intelligents. Ce guide complet s'adresse aux chercheurs, aux professionnels de la sante et aux decideurs politiques pour construire des ecosystemes de sante securises, transparents et centres sur le patient. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: New. Print on Demand.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. PRINT ON DEMAND.

Paperback. Condizione: new. Paperback. Ksiazka "Blockchain-Enabled Federated Learning for Privacy and Security" bada integracje technologii blockchain i federacyjnego uczenia sie w celu sprostania krytycznym wyzwaniom zwiazanym z udostepnianiem danych w opiece zdrowotnej. Wraz z rozwojem elektronicznej dokumentacji medycznej, obrazowania medycznego, urzadzen IoMT i genomiki, ochrona prywatnosci pacjentow przy jednoczesnym umozliwieniu wspolpracy AI stala sie niezbedna. Blockchain zapewnia decentralizacje, niezmiennosc i zaufanie, podczas gdy uczenie federacyjne zapewnia szkolenie modeli bez ujawniania surowych danych. Razem tworza one chroniaca prywatnosc, audytowalna i skalowalna strukture dla sztucznej inteligencji w opiece zdrowotnej. Ksiazka obejmuje podstawy, architektury systemow, techniki kryptograficzne i kompromisy w zakresie wydajnosci, a takze rzeczywiste studia przypadkow w badaniach nad rakiem, IoMT i diagnostyce COVID-19. Podkresla kwestie regulacyjne i etyczne, takie jak RODO, HIPAA i indyjska ustawa DPDP, a takze proponuje przyszle badania w zakresie integracji kwantowej, wyjasnialnej sztucznej inteligencji, FL uwzgledniajacej sprawiedliwosc i zarzadzania za pomoca inteligentnych kontraktow. Ten kompleksowy przewodnik sluzy badaczom, pracownikom sluzby zdrowia i decydentom w budowaniu bezpiecznych, przejrzystych i zorientowanych na pacjenta ekosystemow opieki zdrowotnej. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condizione: new. Paperback. O livro "Blockchain-Enabled Federated Learning for Privacy and Security" explora a integracao da tecnologia blockchain e da aprendizagem federada para enfrentar desafios criticos na partilha de dados de saude. Com o aumento dos registos de saude electronicos, das imagens medicas, dos dispositivos IoMT e da genomica, tornou-se essencial salvaguardar a privacidade dos pacientes e, ao mesmo tempo, permitir a IA colaborativa. O blockchain fornece descentralizacao, imutabilidade e confianca, enquanto o aprendizado federado garante o treinamento do modelo sem expor dados brutos. Juntos, eles formam uma estrutura de preservacao da privacidade, auditavel e escalavel para IA de saude. O livro aborda os fundamentos, as arquitecturas de sistemas, as tecnicas criptograficas e as compensacoes de desempenho, juntamente com estudos de caso do mundo real na investigacao do cancro, na IoMT e no diagnostico da COVID-19. Destaca consideracoes regulamentares e eticas, como o GDPR, HIPAA e a Lei DPDP da India, e propoe pesquisas futuras em integracao quantica, IA explicavel, FL com consciencia de justica e governanca por meio de contratos inteligentes. Este guia abrangente serve investigadores, profissionais de saude e decisores politicos na construcao de ecossistemas de saude seguros, transparentes e centrados no paciente. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condizione: new. Paperback. The book "Blockchain-Enabled Federated Learning for Privacy and Security" explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condizione: new. Paperback. Das Buch "Blockchain-Enabled Federated Learning for Privacy and Security"(Blockchain-gestuetztes foederiertes Lernen fuer Datenschutz und Sicherheit) untersucht die Integration von Blockchain-Technologie und foederiertem Lernen zur Bewaeltigung kritischer Herausforderungen beim Austausch von Gesundheitsdaten. Mit der Zunahme von elektronischen Gesundheitsakten, medizinischer Bildgebung, IoMT-Geraeten und Genomik ist der Schutz der Privatsphaere von Patienten bei gleichzeitiger Ermoeglichung kollaborativer KI unerlaesslich geworden. Blockchain bietet Dezentralisierung, Unveraenderlichkeit und Vertrauen, waehrend foederiertes Lernen das Training von Modellen ohne Offenlegung von Rohdaten gewaehrleistet. Zusammen bilden sie einen datenschutzfreundlichen, ueberpruefbaren und skalierbaren Rahmen fuer KI im Gesundheitswesen. Das Buch behandelt Grundlagen, Systemarchitekturen, kryptografische Techniken und Leistungsabwaegungen sowie Fallstudien aus der Praxis in der Krebsforschung, IoMT und COVID-19-Diagnose. Es werden regulatorische und ethische UEberlegungen wie GDPR, HIPAA und das indische DPDP-Gesetz hervorgehoben, und es werden Vorschlaege fuer die zukuenftige Forschung in den Bereichen Quantenintegration, erklaerbare KI, fairnessbewusste FL und Governance durch intelligente Vertraege gemacht. Dieser umfassende Leitfaden dient Forschern, Fachleuten im Gesundheitswesen und politischen Entscheidungstraegern beim Aufbau sicherer, transparenter und patientenzentrierter Gesundheitsoekosysteme. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condizione: new. Paperback. Il libro "Blockchain-Enabled Federated Learning for Privacy and Security" esplora l'integrazione della tecnologia blockchain e dell'apprendimento federato per affrontare le sfide critiche nella condivisione dei dati sanitari. Con l'aumento delle cartelle cliniche elettroniche, della diagnostica per immagini, dei dispositivi IoMT e della genomica, e diventato essenziale salvaguardare la privacy dei pazienti e al contempo consentire l'IA collaborativa. La blockchain offre decentralizzazione, immutabilita e fiducia, mentre l'apprendimento federato garantisce la formazione dei modelli senza esporre i dati grezzi. Insieme, formano un quadro di riferimento per l'IA in campo sanitario che preserva la privacy, e verificabile e scalabile. Il libro tratta i fondamenti, le architetture di sistema, le tecniche di crittografia e i compromessi sulle prestazioni, insieme a casi di studio reali nella ricerca sul cancro, nell'IoMT e nella diagnosi COVID-19. Il documento mette in evidenza considerazioni di carattere normativo ed etico, come il GDPR, l'HIPAA e il DPDP Act indiano, e propone ricerche future sull'integrazione quantistica, l'IA spiegabile, il FL consapevole dell'equita e la governance tramite contratti intelligenti. Questa guida completa serve ai ricercatori, agli operatori sanitari e ai responsabili politici per costruire ecosistemi sanitari sicuri, trasparenti e incentrati sul paziente. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.