Buch, Englisch, 344 Seiten, Format (B × H): 150 mm x 228 mm, Gewicht: 517 g
Ai, Classification, Wearable Devices, and Computer-Aided Diagnosis
Buch, Englisch, 344 Seiten, Format (B × H): 150 mm x 228 mm, Gewicht: 517 g
ISBN: 978-0-443-13816-4
Verlag: Elsevier Science
Artificial Intelligence in e-health Framework, Volume One: AI, Classification, Wearable Devices, and Computer-Aided Diagnosis 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.
This is a valuable resource for health professionals, scientists, researchers, students, and all who wish to broaden their knowledge in this advancing technology.
Autoren/Hrsg.
Weitere Infos & Material
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