Federated Intelligent System for Healthcare
A Practical Guide
- 313 pages
- English
- PDF
- Available on iOS & Android
Federated Intelligent System for Healthcare
A Practical Guide
About this book
This practical guide gives valuable insights for integrating advanced technologies in healthcare, empowering researchers to effectively navigate and implement federated systems to enhance patient care.
Federated Intelligent Systems for Healthcare: A Practical Guide explores the integration of federated learning and intelligent systems within the healthcare domain. This volume provides an in-depth understanding of how federated systems enhance healthcare practices, detailing their principles, technologies, challenges, and opportunities. Additionally, this book addresses secure and privacy-preserving sharing of medical data, applications of artificial intelligence and machine learning in healthcare, and ethical considerations surrounding the adoption of these advanced technologies. With a focus on practical implementation and real-world use cases, Federated Intelligent Systems for Healthcare: A Practical Guide equips healthcare professionals, researchers, and technology experts with the knowledge needed to navigate the complexities of federated intelligent systems in healthcare and harness their potential to transform patient care and medical advancements.
Readers will find the book:
- Provides cutting-edge research from industry experts to unlock the future of healthcare with innovative insights that embrace federated intelligence and shape the future;
- Presents novel technologies and conceptual and visionary-based scenarios;
- Discusses real-world case studies and implementations that illustrate how federated intelligence is practically applied across various healthcare scenarios, from personalized diagnostics to population-level insights;
- Stands as a pioneer in the exploration of federated intelligent systems in healthcare.
Audience
Data scientists, IT, healthcare and business professionals working towards innovations in the healthcare sector. The book will be especially helpful to students and educators.
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Information
Table of contents
- Cover
- Series Page
- Title Page
- Copyright Page
- Contents
- Preface
- Chapter 1 Introduction to Federated Intelligent Systems in Healthcare
- Chapter 2 Federated Autonomous Deep Learning for Distributed Healthcare System
- Chapter 3 Intelligent Fusion: Federated Learning and Blockchain in Sustainable Healthcare 5.0
- Chapter 4 Foundations of Federated Intelligent Systems in Healthcare
- Chapter 5 Integrating Edge Devices and Internet of Medical Things in Modern Healthcare
- Chapter 6 Cloud Infrastructure and Federated Learning
- Chapter 7 Machine Learning and Artificial Intelligence Fundamentals for Federated Systems
- Chapter 8 Reconstructing Healthcare Foundations: Building Blocks of Federated Systems in Medical Technology
- Chapter 9 Federated Learning in Brain Tumor Segmentation in Medical Imaging
- Chapter 10 Disease Prediction and Early Diagnosis Using Federated Models
- Chapter 11 Navigating Bias and Ensuring Fairness in Federated Learning: An In-Depth Exploration of Data Distribution, IID, and Non-IID Challenges
- Index
- EULA