Next generation healthcare informatics / B. K. Tripathy, Pawan Lingras, Arpan Kumar Kar, Chiranji Lal Chowdhary, editors.
This edited book provides information on emerging fields of next-generation healthcare informatics with a special emphasis on emerging developments and applications of artificial intelligence, deep learning techniques, computational intelligence methods, Internet of medical things (IoMT), optimizati...
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| Other Authors: | , , , |
|---|---|
| Format: | Ebook |
| Language: | English |
| Published: |
Singapore :
Springer,
2022.
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| Series: | Studies in computational intelligence ;
v. 1039. |
| Subjects: | |
| Online Access: | Springer eBooks |
Table of Contents:
- Chapter 1. Methods for the recognition of multisource data in intelligent medicine: A review and next generation trends
- Chapter 2. Deep Learning in Healthcare: Challenges and Opportunities
- Chapter 3. Examination of Health Data Performance Depending on the Creative Use of Optimization Methods and Machine Learning Algorithms
- Chapter 4. Effect of computation and cognitive bias in healthcare intelligence and pharmacogenomics
- Chapter 5. Application of Genetic Algorithms in Healthcare: A Review
- Chapter 6. Decision-Making in Healthcare Nano-informatics
- Chapter 7. A Succinct Analytical Study of the Usability of Encryption Methods in Healthcare Data Security
- Chapter 8. IoMT in healthcare industry Concepts and Applications
- Chapter 9. The Effect of Heuristic Methods Towards Performance of Health Data Analysis
- Chapter 10. AI for Stress Diagnosis at Home Environment
- Chapter 11. Contemporary Technologies to Combat Pandemics and Epidemics
- Chapter 12. Deep Learning for Diabetic Retinopathy Detection: Challenges and Opportunities
- Chapter 13. Deep Reinforcement Based Conversational AI Agent in Healthcare System
- Chapter 14. Deep Learning Empowered Fight against COVID-19: A Survey
- Chapter 15. Application of GAN in Guided Imagery Therapy
- Chapter 16. Digital Transformation in Healthcare Industry: A Survey
- Chapter 17. Application of Deep Learning in Mental Disorder: Challenges and Opportunities.