Handbook of Deep Learning Models for Healthcare Data Processing

Section 1: Emerging Technologies of Deep Learning in Healthcare. 1. Deep Learning Models for Electronic Health Record (EHR) Data Analysis. 2. An Extensive Study of Disease Prediction Models using Machine Learning. 3. Deep Learning Approaches for Alzheimer's disease Diagnosis: A Comparative Study of ResNet50, CNN, and MobileNet. 4. Sentiment Classification Analysis Using Deep Learning Network Models. 5. Predictive Modeling of Herbal-Drug Interactions using Mathematical Approaches. 6. Revolutionizing Breast Cancer Detection: A Shallow Neural Network Approach for Accurate Classification of Calcifications and Masses in Mammographic Scans. 7. Artificial Intelligence-Based Automated Detection of Rheumatoid Arthritis: A Review. 8. Medical Imaging Analysis Techniques: Advances, Challenges, and Future Directions. 9. Modeling the Transtheoretical Model for Health Behavior Stage Analysis: Tool Development and Testing. Section 2: Deep Learning Analytics in Healthcare. 10. Utilization of OCR and LLM to decode medical diagnostics/prescriptions into general-purpose language. 11. A state-of-the-art model for drug classification using image recognition. 12. Transforming Healthcare with Blockchain-based Smart Contracts: A Focus on Quality-of-Service. 13. Prototype Model for Face and Skin-Related Disease Detection Using Deep Learning and Image Recognition. 14. Brain Computer Interface (BCI)-Inspired Arduino Based Robotic Brain Controller. 15. Transfer Learning-based Framework for Human Skin Cancer Evaluation . 16. Healthcare Reimagined: AI's Impact on Diagnosis and Treatment. 17. Advanced LSTM Approach for Aspect-based Sentiment Classification. 18. A Review on Patch-based Medical Image Classification using Convolutional Neural Network (CNN).