UID:
almahu_9949882722802882
Format:
XXI, 394 p. 144 illus., 113 illus. in color.
,
online resource.
Edition:
1st ed. 2024.
ISBN:
9783031650222
Series Statement:
Information Systems Engineering and Management, 7
Content:
This book showcases an endeavor to delve into the fusion of artificial intelligence (AI) and the Internet of Things (IoT) within the healthcare domain. The healthcare sector is currently experiencing a shift fueled by technological advancements and a heightened focus on providing tailored, efficient and impactful care to individuals. AI and IoT have emerged as facilitators of this evolution presenting opportunities to elevate patient results streamline operations and enhance decision-making within healthcare environments. This publication unites an array of viewpoints from experts in healthcare, technology and research domains. Through an array of enlightening chapters readers will embark on a journey exploring the applications, hurdles and consequences of merging AI with IoT in healthcare contexts. From analytics and remote monitoring to treatment suggestions and operational enhancements the potentials offered by AI and IoT is both captivating and revolutionary. As editors overseeing this volume's creation we take pride in presenting an assemblage of contributions that mirror the research findings, innovations and optimal practices in healthcare technology. Our aim is to encourage readers to engage in thinking, creativity and teamwork when considering the impact of integrating AI with IoT on enhancing patient care and healthcare services.
Note:
Chapter 1. PATIENT HEALTH SERVICES FOR EARLY DETECTION THERAPY OF DIABETES MELLITUS WITH EXPERT SYSTEM AND IOT -- Chapter 2. Exploring AI and IoT Integration for Medicine Recommendation with Chimp Optimized Dynamic XGBoost (CO-DXB) -- Chapter 3. Integrating IoT and AI in Healthcare: A Novel MS-GNN Framework for Disease Diagnosis -- Chapter 4. Advancing Glioblastoma Treatment through AI-Driven Radiomics: A Comparative Study of Feature Selection and Machine Learning Techniques -- Chapter 5. Utilizing Artificial Intelligence for Enhanced Healthcare Diagnosis and Treatment -- Chapter 6. Artificial Intelligence in Personalized Health Services for Better Patient Care -- Chapter 7. Transforming Healthcare: The Synergistic Fusion of AI and IoT for Intelligent, Personalized Well-being -- Chapter 8. Machine Learning-Based Autism Spectrum Disorder Prediction: A Comparative Approach -- Chapter 9. The Future of Healthcare: Using AI and IoT to Drive Data Driven Revolution -- Chapter 10. Preventive Health Care System for Early Heart Disease Detection using IoT and Machine Learning -- Chapter 11. IoT in Daily Life: Investigating the Impact of IoT on Procrastination, Well-being, Mental Health, and Healthcare Wizards -- Chapter 12 . AI Innovations in Health Care: Reshaping Diagnostics and Care -- Chapter 13. Statistical Distribution of Blood Glucose Levels in Diabetic Patients Diagnosis Using ML-Based PCA Methods -- Chapter 14. IoT-Infused Care: Disentanglement Family Dynamics and Coping Strategies in the Realm of Intellectually Disabled Children -- Chapter 15. An Approach to Pattern Prediction and Early Recognition of Lung Cancer Employing Machine Learning Techniques -- Chapter 16. Unlocking the Potential: Biometric Traits in Healthcare with a Focus on Eye Diseases -- Chapter 17. Pixels, Perspectives, and Psychological Strain: Unravelling the Link Between Negative Body Image, Internet of Things (IOT), and Mental Health Challenges in Student Population -- Chapter 18. DNA-Based Secure Image Transmission Framework Using Encryption and LSB Steganography -- Chapter 19. Building Predictive Models for Cardiovascular Health -- Chapter 20. Transforming Healthcare: The Convergence of IoT and AI.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783031650215
Additional Edition:
Printed edition: ISBN 9783031650239
Additional Edition:
Printed edition: ISBN 9783031650246
Language:
English
DOI:
10.1007/978-3-031-65022-2
URL:
https://doi.org/10.1007/978-3-031-65022-2
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