Soft Computing Techniques in Connected Healthcare Systems
eBook - ePub

Soft Computing Techniques in Connected Healthcare Systems

  1. 292 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Soft Computing Techniques in Connected Healthcare Systems

About this book

This book provides an examination of applications of soft computing techniques related to healthcare systems and can be used as a reference guide for assessing the roles of various techniques. Soft Computing Techniques in Connected Healthcare Systems presents soft computing techniques and applications used in healthcare systems, along with the latest advancements. The authors examine how connected healthcare is the essence of combining a practical operative procedure of interconnectedness of electronic health records, mHealth, clinical informatics, electronic data exchange, practice management solutions, and pharmacy management. The book focuses on different soft computing techniques, such as fuzzy logic, ANN, and GA, which will enhance services in connected health systems, such as remote diagnosis and monitoring, medication monitoring devices, identifying and treating the underlying causes of disorders and diseases, improved access to specialists, and lower healthcare costs. The chapters also examine descriptive, predictive, and social network techniques and discuss analytical tools and the important role they play in enhancing the services to connected healthcare systems. Finally, the authors address real-time challenges with real-world case studies to enhance the comprehension of topics. This book is intended for under graduate and graduate students, researchers, and practicing professionals in the field of connected healthcare. It provides an overview for beginners while also addressing professionals in the industry on the importance of soft computing approaches in connected healthcare systems.

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Yes, you can access Soft Computing Techniques in Connected Healthcare Systems by Moolchand Sharma,Suman Deswal,Umesh Gupta,Mujahid Tabassum,Isah Lawal,Isah A. Lawal in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Biomedical Science. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication
  7. Table of Contents
  8. Editors’ Profile
  9. Contributors
  10. Preface
  11. About the Book
  12. Chapter 1 Automation in Healthcare Forecast and Outcome: A Case Study
  13. Chapter 2 Optimizing Smartphone Addiction Questionnaires with Smartphone Application and Soft Computing: An Intelligent Smartphone Usage Behavior Assessment Model
  14. Chapter 3 Artificial Neural Network Model for Automated Medical Diagnosis
  15. Chapter 4 Analyzing of Heterogeneous Perceptions of a Mutually Dependent Health Ecosystem System Survey
  16. Chapter 5 Intuitionistic Fuzzy-Based Technique Ordered Preference by Similarity to the Ideal Solution (TOPSIS) Method: An MCDM Approach for the Medical Decision Making of Diseases
  17. Chapter 6 Design of a Heuristic IoT-Based Approach as a Solution to a Self-Aware Social Distancing Paradigm
  18. Chapter 7 Combined 3D Mesh and Generative Adversarial Network–Based Improved Liver Segmentation in Computed Tomography Images
  19. Chapter 8 Applying Privacy by Design to Connected Healthcare Ecosystems
  20. Chapter 9 Next-Generation Platforms for Device Monitoring, Management, and Monetization for Healthcare
  21. Chapter 10 Real-Time Classification and Hepatitis B Detection with Evolutionary Data Mining Approach
  22. Chapter 11 Healthcare Transformation Using Soft Computing Approaches and IoT Protocols
  23. Chapter 12 Automated Detection and Classification of Focal and Nonfocal EEG Signals Using Ensemble Empirical Mode Decomposition and ANN Classifier
  24. Chapter 13 Challenges and Future Directions of Fuzzy System in Healthcare Systems: A Survey
  25. Chapter 14 Perceptual Hashing Function for Medical Images: Overview, Challenges, and the Future
  26. Chapter 15 Deploying Machine Learning Methods for Human Emotion Recognition
  27. Chapter 16 Maternal Health Risk Prediction Model Using Artificial Neural Network
  28. Index