Artificial Intelligence in Healthcare - Bathla, Gourav; Kumar, Sanoj; Garg, Harish;(ed.) - Prospero Internet Bookshop
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Artificial Intelligence in Healthcare

Emphasis on Diabetes, Hypertension, and Depression Management
 
Edition number: 1
Publisher: CRC Press
Date of Publication:
 
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GBP 120.00
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Short description:

This book presents state-of-the-art research works for a better understanding of the advantages and limitations of AI techniques in the field of healthcare. It will further discuss artificial intelligence applications in depression, hypertension and diabetes management.


Long description:

This book presents state-of-the-art research works for a better understanding of the advantages and limitations of AI techniques in the field of healthcare. It will further discuss artificial intelligence applications in depression, hypertension and diabetes management. The text also presents an artificial intelligence chatbot for depression, diabetes, and hypertension self-help.


This book:



  • Provides a structured overview of recent developments of artificial intelligence applications in the healthcare sector.                                                                                          

  • Presents an in-depth understanding of how artificial intelligence techniques can be applied to diabetes management.                                                                                      

  • Showcases supervised learning techniques based on datasets for depression management.

  • Discusses artificial intelligence chatbot for diabetes, depression, and hypertension self-care.

  • Highlights the importance of artificial intelligence in managing and predicting diabetes, hypertension, and depression.


The text is primarily written for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering.

Table of Contents:

1. Artificial Intelligence and Digital Health Twin Applications in Healthcare ? A Systematic Review. 2. Early Detection of Diabetic Foot Ulcers Using Optical Flow Based Ensemble Learning CNN Framework. 3. Identification of potential biomarkers for diabetes mellitus using Gene expression datasets, Machine learning, and R packages to predict the risk for diabetes. 4. Machine learning for chronic diseases. 5. AI Chatbot For Diabetes Self-Help. 6. Future of Diabetic Management Using Artificial Intelligence. 7. Detection of Generalized Anxiety Disorder. 8. Machine learning techniques for prediction of hypertension. 9. Food recommendation for hypertensive persons. 10. Optimized Support Vector Machines for Detection of Mental Disorders. 11. Artificial Intelligence Applications in depression management. 12. Depression Prediction Using Machine Learning Techniques. 13. Future of depression management using Artificial Intelligence. 14. AI chatbot for depression self-help. 15. Artificial Intelligence in Healthcare: Futuristic Opportunities.