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Revolutionizing Healthcare: AI Integration with IoT for Enhanced Patient Outcomes
Title
Revolutionizing Healthcare: AI Integration with IoT for Enhanced Patient Outcomes [electronic resource] / edited by Shashi Kant Gupta, Dimitrios A. Karras, Rajesh Natarajan.
ISBN
9783031650222
Edition
1st ed. 2024.
Publication
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Physical Description
1 online resource (XXI, 394 p.) 144 illus., 113 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ENIN.
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Format
Books / Online
Language
English
Added to Catalog
October 14, 2024
Series
Information Systems Engineering and Management, 7
Contents
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.
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