Main description:

Intelligent IoT Systems in Personalized Health Care delivers a significant forum for the technical advancement of IoMT learning in parallel computing environments across biomedical engineering diversified domains and its applications. Pursuing an interdisciplinary approach, the book focuses on methods used to identify and acquire valid, potentially useful knowledge sources. The book presents novel, in-depth, fundamental research contributions from a methodological/application perspective to help readers understand the fusion of AI with IoT and its capabilities in solving a diverse range of problems for biomedical engineering and its real-world personalized health care applications.

The book is well suited for researchers exploring the significance of IoT based architecture to perform predictive analytics of user activities in sustainable health.

Contents:

1. Combining IoT architectures in next generation healthcare computing systems 2. RFID-based unsupervised apnea detection in health care system 3. Designing a cooperative hierarchical model of interdiction median problem with protection and its solution approach: A case study of health-care network 4. Parallel machine learning and deep learning approaches for internet of medical things (IoMT) 5. Cloud-based IoMT framework for cardiovascular disease prediction and diagnosis in personalized E-health care 6. A study on security privacy issues and solutions in internet of medical things - A review 7. Application of computational intelligence models in IoMT big data for heart disease diagnosis in personalized health care 8. An improved canny detection method for detecting human flexibility 9. Prediction and classification of diabetes mellitus using genomic data 10. An application of cypher query-based dynamic rule-based decision tree over suicide statistics dataset with Neo4j 11. Exploring the possibilities of security and privacy issues in health-care IoT