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| Link zu diesem Datensatz | https://d-nb.info/1389201015 |
| Titel | The Convergence of Federated Learning and Healthcare 5.0 and Beyond: A New Era of Intelligent Health Systems / edited by Wasswa Shafik, Pushan Kumar Dutta, Priyadarshini Pattanaik |
| Person(en) |
Shafik, Wasswa (Herausgeber) Dutta, Pushan Kumar (Herausgeber) Pattanaik, Priyadarshini (Herausgeber) |
| Organisation(en) | SpringerLink (Online service) (Sonstige) |
| Ausgabe | 1st ed. 2026 |
| Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2026 |
| Umfang/Format | Online-Ressource, XVI, 891 p. 97 illus., 83 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-032-03984-2 Printed edition:: ISBN: 978-3-032-03986-6 Printed edition:: ISBN: 978-3-032-03987-3 |
| Inhalt | Understanding Healthcare 5.0 and Emerging Technologies -- Fundamentals of Federated Learning: Principles and Applications -- Data Privacy Challenges in Artificial Intelligence-Driven Healthcare -- Regulatory Frameworks: HIPAA, GDPR, and Compliance in Federated Learning -- Real Time Patient Monitoring and IOMT Applications -- Integration of Blockchain Technology for Ensuring Trust and Security in the Digital Health Market: A Comprehensive Review -- The Convergence of Federated Learning for the Digital Healthcare Market: An Overview -- Differential Privacy and Homomorphic Encryption in Healthcare Artificial Intelligence -- Analysis of Consumer Emotions Impacted By COVID-19 -- Guiding The Development of AI In Healthcare Through Ethical Considerations and Effective Governance -- Intelligent Workforce Management in Healthcare 5.0: Redefining HR Through Federated Learning -- The Legal Labyrinth of Smart Wearable Medical Devices: A Literary Overview -- From Traditional to Intelligent: Transforming Global Health Care through Innovation -- Ethical Considerations of Emotion AI used in the Synthetic Media Generations and Applications -- Machine Learning-Based Prediction of Gene-Disease Associations for Reliable Evidence -- Addressing Computational Overhead in Federated Learning Models in Healthcare 5.0 and Beyond -- Robustness Against Adversarial Attacks and Model Security in Healthcare 5.0 and Beyond.-Scalable Model Aggregation and Interoperability Solutions in Healthcare Systems -- Federated Learning for Decentralized Healthcare: Privacy, Efficiency, and Scalability in Healthcare 5.0 -- Federated Learning Architectures: Centralized Vs. Decentralized Models In Human Resource(HR) -- A Two-staged Optimized Stacking Ensemble learning Classifier for the Prediction of Cervical Cancer -- AI-Assisted Histopathological Image Analysis for Automated Gastric Cancer Detection -- Robotics and AI-Powered Surgical Interventions in Gastric Cancer: Enhancing Precision and Efficacy of Oncologic Treatment24. Electronic Health Records using Blockchain -- Centralized vs. Decentralized Federated Learning Architectures: Design Trade-offs, Security, and Performance in Healthcare 5.0 Applications -- Navigating Healthcare 5.0: How Emerging Technologies Are Transforming Care Delivery and Medical Innovation -- Identification of Stress in IT Professionals Using Convolutional Neural Network -- Federated Learning for Precision Medicine: A Blockchain Enhanced Framework for Privacy Preserving Predictive Analytics in Healthcare 5.0 -- Machine Learning Advancements for Diabetes Prediction with LightGBM -- Blockchain Integration for Enhanced Trust and Security in Federated Learning for Healthcare 5.0 -- Ontology-Based Data Harmonization and Federated Transfer Learning: Enabling Scalable and Interoperable Intelligence in Healthcare 5.0 for Next-Generation Healthcare -- Future Trends in Federated Learning for Next-Generation Healthcare -- Advancing Federated Learning in Healthcare 5.0 -- A Futuristic Pathway in Healthcare -- Federated Learning in Healthcare Finance: A Systematic Review of Privacy-Preserving Models -- AI-Induced Digital Addiction: Its Impact on Human Relationships within Healthcare 5.0 Ecosystems -- Real-Time Detection of Latent Infections Using LSTM and IoMT-Based Health Monitoring -- Federated Learning and Healthcare 5.0: Paving the Road Ahead for Privacy-Preserving Smart Health Systems -- Neuro-Symbolic Federated Learning Models for Diagnostic Intelligence in Healthcare 5.0 -- Reducing Computational Overhead in Federated Learning: A Comprehensive Analysis -- Future Trends in Federated Learning: Enabling Secure and Personalized Healthcare Solutions |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2602070307084.205916382015 DOI: 10.1007/978-3-032-03985-9 |
| URL | https://doi.org/10.1007/978-3-032-03985-9 |
| ISBN/Einband/Preis | 978-3-032-03985-9 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Studies in Computational Intelligence ; 1247 |
| Sachgruppe(n) | 360 Soziale Probleme, Sozialdienste, Versicherungen |
| Online-Zugriff | Archivobjekt öffnen |
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