About the Book:
In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity.
Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges.
This book is useful for research scholars and students involved in critical condition analysis and computation models.
Table of Contents
1. Machine Learning in Healthcare.2. Feature Extraction and Applications of Bio Signals.
3. Machine Learning Methods for Managing Parkinson-s Disease. 4. Challenges of Medical Text and Image Processing.5. Machine Learning Solutions in Computer-Aided Medical Diagnosis.6. Rule Learning in Healthcare and Health Services Research.7. Diagnosis in Medical Imaging.8. Identifying Diseases and Diagnosis Using Machine Learning.9. Machine Learning-Based Behavioral Modification.10. Smart Health Records11. Treatment Recommendation System12. Smart Health Informatics System
13. Natural Language Processing Utilization in Healthcare14. Clinical Decision Support and Predictive Analytics15. Bioinformatics and Biometrics16. Human Computer Interfaces and Usability17. Education and Capacity Building
18. Learning Analytics for Competence Assessment
19. Patient Simulators20. Serious Gaming
21. Patient Empowerment and Engagement22. Social Media, Mobile Apps, and Patient Portals23. Human Factors and Technology Adoption24. Surveillance System25. Robotics26. Object Detection
27. Traffic Analysis28. Big Data in Healthcare Systems29. Advanced Decision-Making and Data Analytics30. Emergence of Decision Support Systems31. Big Data Based Frameworks and Machine Learning32. Predictive Analysis and Modeling
33. Security and Privacy with Machine Learning Systems34. Role of Social Media in Healthcare Analytics35. Big Data Based Case Studies for Healthcare Analytics36. Machine Learning and Deep Learning Paradigms and Case Studies37. Machine Learning in Agriculture
