Bültmann & Gerriets
Artificial Intelligence in E-Health Framework, Volume 1
Ai, Classification, Wearable Devices, and Computer-Aided Diagnosis
von Sudip Paul, Jasjit Suri
Verlag: Elsevier Science
Taschenbuch
ISBN: 978-0-443-13816-4
Erscheint im September 2025
Sprache: Englisch
Umfang: 625 Seiten

Preis: 180,50 €
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Klappentext
Inhaltsverzeichnis

Artificial Intelligence in e-health Framework, Volume 1: Classification, Wearable Devices, Computer-Aided Diagnosis, E-Health Records presents a variety of AI techniques and applications for solving issues in the healthcare industry. As Artificial Intelligence is increasingly incorporated into medical systems and methods, it is critical to understand the formulations and basics of machine and deep learning as well as how to implement these advances into practice. This book specifically explores Artificial Intelligence developments in disease diagnosis, health monitoring, medical image recognition and diagnostics, as well as e-health records management. It is a valuable resource for health professionals, scientists and researchers, students, and all who wish to broaden their knowledge in this advancing technology.



Section 1: Introduction to Artificial Intelligence 1. Data Processing 2. Regression, Classification, and Clustering Algorithms 3. Deep Learning Section 2: Application of Artificial Intelligence in Disease Diagnosis 4. Application of Artificial Intelligence in Pioneering Heart Disease Detection 5. From Data to Diagnosis: Leveraging Machine Learning for Heart Disease Classification with the Cleveland Heart Disease Dataset 6. AI-based Treatment Solutions 7. Application of AI in Big Data Management Section 3: AI in Health Monitoring and Wearables Devices 8. Remote Health Monitoring Using Artificial Intelligence 9. Predicting Women’s Fertility with AI 10. A Comparative Study on "Face Mask Detection" Using Machine Learning and Deep Learning Algorithms 11. Enhancing Communication: A Review on AI Wearables for the Deaf and Mute 12. AI based cuffless digital sphygmomanometric measuring system for chronic illness patients Section 4: Application of AI Medical Image Recognition 13. Identifying Cardiovascular Abnormalities 14. Non-linear Activation Functions of CNN for Classification of MRI Brain tumor Images 15. Artificial Intelligence-Based Management Prospects of Neurological Disorders with Special Reference to Epilepsy 16. Screening for Common Cancers