Healthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities
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Healthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities

Healthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities

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About the Book

Healthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities presents the applications of the healthcare sector in the context of futuristic smart cities. It explores various applications like the advancements in computational and network models along with the innovative paradigms for an able healthcare model. The book discusses the state-of-the-art intelligent network and computing paradigms and machine learning models for robust healthcare. This book is for academicians, researchers, and entrepreneurs working on healthcare-driven intelligent computing paradigms to secure futuristic smart cities. It includes several aspects of the challenges faced by a futuristic smart city in healthcare, includes challenges emanating from the immense data generated by the wearable sensors, data analysis, and security concerns owing to the patient-related data. It works as a pertinent resource on how cutting-edge technologies can be integrated to aptly provide solutions for the numerous challenges faced by the healthcare industry. Includes several use cases, practical challenges, and solutions for executing smart healthcare. Features Covers a multitude of computing paradigms viz; Cloud computing, Fog Computing, and Mist Computing Healthcare is discussed leveraging smart city, so it can potentially identify the gaps and present some newer use cases to handle future pandemics The network aspect is also covered with an inclusion of the next-generation paradigm which is Software Defined Networking (SDN) Security and privacy issues are considered, which is crucial to handle security-related aspects Machine Learning models are also discussed to provide any entrepreneur develop a business model involving cutting-edge technologies This book is for academicians, researchers, and entrepreneurs working on healthcare-driven intelligent computing paradigms to secure futuristic smart cities.

Table of Contents:
1. Healthcare and its Applications in a Smart City. 2. Role of Body-Transfer System in Active Assistive Living for Effective Healthcare. 3. An in depth analysis of machine learning and artificial intelligence advancements in healthcare for smart cities. 4. Comprehensive Survey of IoT, Machine Learning, and Reliability Engineering for Health Care Applications. 5. Artificial Intelligence based Solutions for Optimized Data Routing through Multi-hop Healthcare Sensor Networks. 6. AIoMT: An AI Based Network Selection Framework for Next-Generation enabled IoMT Network in Smart City. 7. Concurrent Clustering with Outlier Removal in Healthcare. 8. Cluster Weighting-A New Clustering Technique for Outlier Removal and Noise Overlap in Healthcare Diagnosis for Smart City. 9. Cluster Weighting-A New Clustering Technique for Outlier Removal and Noise Overlap in Healthcare Diagnosis for Smart City. 10. Pneumonia classification in Chest X-ray Images Using Fusion of Deep Features and LightGBM. 11. AI-Driven Prioritization and Detection of Covid-19 Cases in Smart Cities: An Integration of X-Ray Imaging and ResNet18 Machine Learning. 12. Depression detection in social media text using machine learning techniques. 13. Depression Symptoms Prediction on Online Social Networks Using Machine Learning Algorithms. 14. A Sorting Strip based Body worn Antenna for Assisting Breast Cancer Detection for a smart Healthcare environment. 15. Artificial Intelligence Prediction of the Risk of Ovarian Cancer at an Early Stage in Smart Cities. 16. Chatbot Enable Brain Cancer Prediction using Convolutional Neural Network for Smart Health Care. 17. Federated Learning for Heart Disease Detection in Smart Healthcare: A Survey. 18. Federated Learning for Heart Disease Detection Using a Grey Wolf Transfer Learning Model Based on Multi-Perceptron Neural Networks. 19. A novel Mist-Fog federated learning model for heart disease detection in smart healthcare. 20. Energy-efficient and Delay Tolerant Prediction of Heart Disease in IoT-enabled Mist Computing Platforms.


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Product Details
  • ISBN-13: 9781032626895
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman & Hall/CRC
  • Height: 234 mm
  • No of Pages: 366
  • Width: 156 mm
  • ISBN-10: 1032626895
  • Publisher Date: 18 Dec 2024
  • Binding: Hardback
  • Language: English
  • Weight: 770 gr


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Healthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities
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Healthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities
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