
IoT and AI-Enabled Healthcare Solutions for Intelligent Disease Prediction
- English
- ePUB (mobile friendly)
- Available on iOS & Android
IoT and AI-Enabled Healthcare Solutions for Intelligent Disease Prediction
About this book
The book presents fundamental to advanced concepts of AI and IoT in healthcare and disease prediction, demonstrating the emerging mechanisms, including machine learning, deep learning, image sensing, and explainable AI models to handle issues in healthcare industries with real-life scenarios. Included chapters are contributed by experienced professionals and academicians who examine severe diseases, applications, models, tools, frameworks, case studies, applications, and best practices in Healthcare. This book integrates the medical domain with AI technology. It covers trending explainable AI, computer vision (CV), and IoT that facilitate automation for healthcare solutions and medical diagnostics. The primary focus on explainable AI uncovers the black box of deep learning and bridges the distance between medical professionals and technologists. IoT in Healthcare: provides a mechanism of image sensing and is helpful in surgical tools.
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Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Preface
- Contents
- 1. Introduction to IoT and AI for Providing Healthcare Solutions
- 2. Seeing Beyond Symptoms Utilizing Machine Learning Techniques for Early Diabetes Diagnosis
- 3. A Decent ML-Based System for Cardiovascular Disease Detection
- 4 Breast Cancer Detection Using Explainable Artificial Intelligence
- 5. Deep Learning Applications for Chronic Disease Detection and Prevention
- 6 Glaucoma Detection Using Retinal Images Employing Machine Learning (ML) Algorithms
- 7. Design and Development of Intelligent Systems for Skin Cancer Detection
- 8. IoT Enabled System for Regulating Medical Efficiency and Healthcare Services
- 9. Tumor Prediction Using MRI Images Employing Deep Neural Network
- 10. Nanorobots in the Treatment of Cancer: A Revolutionizing and Precision Medicine With Advantages and Limitations
- 11. Methods of Explainable AI for Continuum Blood Glucose Monitoring with Various Challenges and Future Research Direction
- 12. IoT and AI-based Intelligent Management of Heart Rate Monitoring
- 13. Brain Tumor Prediction using MRI Images Employing Convolutional Neural Network (CNN)
- 14. Decision Support System for Miscarriage Rate Prediction
- Index