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Written as a guide for assessing the roles that these technqiues play, the book highlights implementation strategies, problem solving solutions, and paves the way for future research endeavors in smart and next generation healthcare systems.
1. Computational Intelligence for Healthcare. 2. Analysis of Recurrent Neural Network and Convolution Neural Network Techniques in Blood Cell Classification. Chapter 3. Evaluating the Effectiveness of the Convolution Neural Network in Detecting Brain Tumors. Chapter 4. Implementation of Machine Learning in Color Perception and Psychology: A Review. Chapter 5. Early Recognition of Dynamic Sleeping Patterns Associated with Rapid Eyeball Movement Sleep Behavior Disorder of Apnea Pateants Using Neural Network Techniques. Chapter 6. Smart Attendance cum Health Check-up Machine for Students/Villagers/Company Employees. Chapter 7. Oral Histopathological Photomicrograph Classification Using Deep Learning. Chapter 8. Prediction of Stage of Alzheimer's Disease DenseNet Deep Learning Model. Chapter 9. An Insight of Deep Learning Applications in the Healthcare Industry. Chapter 10. Expand Patient Care with AWS Cloud for Remote Medical Monitoring. Chapter 11. Privacy and Security Solution in Wireless Sensor Network for IoT in Healthcare System. Chapter 12. An Epileptic Seizure Detection and Classification Based on Machine Learning Techniques. Chapter 13. Analysis of Coronary Artery Disease Using Various Machine Learning Techniques.
