Metaverse and AI in Healthcare : A Federated Learning Approach

ホーム
> 洋書
> 英文書
> Medical

個数：

予約

Metaverse and AI in Healthcare : A Federated Learning Approach

Moy Chatterjee, Jyotir (EDT)/ Mahajan, Shubham (EDT)

ウェブストア価格 ¥43,929（本体¥39,936）
Academic Press Inc（2026/05発売）
外貨定価 US$ 200.00
ポイント 399pt

現在予約受付中です。出版後の入荷・発送となります。
（重要：表示されている発売日は予定となり、発売が延期、中止、生産限定品で商品確保ができないなどの理由により、ご注文をお取消しさせていただく場合がございます。予めご了承ください。）

●3Dセキュア導入とクレジットカードによるお支払いについて

≪洋書のご注文について≫ 「海外取次在庫あり」「国内在庫僅少」および「国内仕入れ先からお取り寄せいたします」表示の商品でもクリスマス前(12/20～12/25)および年末年始までにお届けできないことがございます。あらかじめご了承ください。

【入荷遅延について】
世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。

◆画像の表紙や帯等は実物とは異なる場合があります。

◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
また、洋書販売価格は、ご注文確定時点での日本円価格となります。
ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。

製本 Paperback:紙装版/ペーパーバック版／ページ数 400 p.
言語 ENG
商品コード 9780443449581

Full Description

Metaverse and AI in Healthcare: A Federated Learning Approach addresses the transformative integration of artificial intelligence and metaverse technologies in healthcare. It fills a critical gap by exploring how federated learning enables secure, decentralized data sharing and personalized medicine in virtual health platforms, meeting urgent demands for privacy, interoperability, and innovation. The book is structured into four parts covering foundational AI and federated learning concepts, augmented reality and metaverse applications, legal and cybersecurity challenges, and emerging strategic trends. Contributors from academia and industry present chapters on predictive modeling, cybersecurity frameworks, AR fitness, legal perspectives, and AI-driven medical tourism, supported by case studies and technical explanations. This reference equips graduate students, researchers, and professionals in academia and industry who specialize in computer science, federated learning, biomedical engineering, and digital healthcare with practical knowledge and forward-looking analysis. It empowers readers to navigate evolving digital health ecosystems, addressing data privacy, customized care, and global access challenges through federated learning and metaverse solutions.

Part 1: AI and Federated Learning Foundations in Healthcare
1. Introduction to the Convergence of Metaverse, AI, and Federated Learning in Healthcare
2. Exploring the Potential of Deep Learning for Transcription Factor Binding in Deoxyribose Nucleic Acid
3. Predictive Modeling of Alzheimer's Disease using MRI Images & Machine Learning Algorithms
4. Heart Disease Prediction using RBA: A Weighted Rivalry-Based Ensemble Learning Approach
5. Federated Learning and Machine Learning for the Detection of Heart Diseases
6. Predictive Modelling for Disease Prevention
7. A Resilient Federated Learning-Based Cybersecurity Framework for Healthcare Systems
Part 2: Metaverse and Augmented Reality in Healthcare
8. ARFIT: Redefining Fitness through Immersive Augmented Reality Experiences
9. Metasports in the Metaverse Era: A New Frontier for Athlete Performance and Health
10. Augmented Reality for Pediatric Rehabilitation: Legal Considerations for Disabled Children in India
11. Metaverse-Enabled Digital Twins: Building Intelligent and Ethical Healthcare Systems
Part 3: Legal, Ethical, and Cybersecurity Challenges
12. A Critical Evaluation of Blockchain Integration in Smart Healthcare System
13. Legal Perspectives on Cybersecurity for Digital Health Platforms Serving Disabled Children in India
14. Mitigating Bias in AI-Driven Burnout Risk Predictions for Optimal Staff Scheduling in Healthcare
Part 4: Strategic and Emerging Trends
15. Improving Cardiac MRI Analysis through Real-time Object Detection with YOLOv8
16. Digital Twin-Driven Cancer Survival Prediction: Machine Learning and EHR Integration for Smart Hospitals
17. ChatGPT in Medicine: Partnering with Doctors for Better Healthcare
18. Artificial Intelligence Based Medical Tourism in 2024 and Beyond: Emerging Trends, Challenges, and Strategic Imperatives