Artificial Intelligence in e-Health Framework, Volume 1: AI, Classification, Wearable Devices, and Computer-Aided Diagnosis
Editat de Sudip Paul, Jasjit S. Surien Limba Engleză Paperback – 27 ian 2025
This is a valuable resource for health professionals, scientists, researchers, students, and all who wish to broaden their knowledge in this advancing technology.
- Provides an in-depth introduction to Artificial Intelligence in e-health framework
- Reviews theoretical and application information to develop understanding of AI advances in diagnostics, health monitoring, and records management
- Discusses advanced AI techniques in both machine learning and deep learning for solving healthcare industry issues
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Specificații
ISBN-13: 9780443138164
ISBN-10: 0443138168
Pagini: 344
Dimensiuni: 152 x 229 x 19 mm
Greutate: 0.52 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0443138168
Pagini: 344
Dimensiuni: 152 x 229 x 19 mm
Greutate: 0.52 kg
Editura: ELSEVIER SCIENCE
Cuprins
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
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