Intelligent Interactive Multimedia Systems for E-Healthcare Applications

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This new volume explores how the merging of interactive multimedia with artificial intelligence has created new and advanced tools in healthcare. It looks at how the latest technologies (artificial intelligence, deep learning, machine learning, big data, IoT, smart device, etc.) help to manage health data, diagnose health issues, monitor treatment, predict pandemic diseases, and more. The book covers several important applications of multimedia in healthcare, including for data visualization purposes, for computer vision for elder healthcare monitoring, for detection of lung nodules, for management systems using machine learning techniques, and for fusion applications in medical image processing. The chapter authors discuss using data mining and machine learning techniques for COVID-19 diagnosis and prediction, in detecting knee osteoarthritis using texture descriptor algorithms, in applying algorithms in fetal ECG enhancement using blockchain for wearable internet of things in healthcare, and more. A chapter also reviews how doctors can make good use of genomics and genetic data through advanced technology. The book concludes with discussions of open issues, challenges, and future research directions for using intelligent interactive multimedia in healthcare. Key features Provides an in-depth understanding of emerging technologies and integration of artificial intelligence, deep learning, big data, IoT in healthcare Details specific applications for the use of AI, big data, and IoT in healthcare Discusses how AI technology can help in formulating protective measures for COVID-19 and other diseases Includes case studies Intelligent Interactive Multimedia Systems for e-Healthcare Applications will be valuable to undergraduate and graduate students planning their careers in either industry or research and to software engineers for using multimedia with artificial intelligence, deep learning, big data, and IoT for healthcare applications.

Author(s): Shaveta Malik, Amit Kumar Tyagi
Publisher: CRC Press/Apple Academic Press
Year: 2022

Language: English
Pages: 460
City: Palm Bay

Cover
Half Title
Title Page
Copyright Page
About the Editors
Table of Contents
Contributors
Abbreviations
Preface
Introduction
Part 1: Introduction of Multimedia in Healthcare Applications
1. Data Visualization for Healthcare
2. Health Monitoring and Management System Using Machine Learning Techniques
3. A Study on Fusion Methods and Their Applications in Medical Image Processing
4. A Study on an Elderly Caretaker Bot Using Computer Vision and Artificial Intelligence
5. Knowledge Shift for Candidate Categorization in Lung Nodule Detection Using 3D Convolutional Neural Network
Part 2: Methods and Techniques for Supporting Multimedia Systems for e-Healthcare
6. Data Mining Techniques: Risk-Wise Classification of Countries toward Prediction and Analysis of Worldwide COVID-19 Dataset
7. Mathematical Model of COVID-19 Diagnosis Prediction Using Machine Learning Techniques
8. Detection and Classification of Knee Osteoarthritis Using Texture Descriptor Algorithms
9. Sensor Cloud-Based Theoretical Machine Learning Models for Predicting Pandemic Diseases
Part 3: Applications for Intelligent and Automated Healthcare Systems
10. Applications of Machine Learning Algorithms in Fetal ECG Enhancement for E- Healthcare
11. Blockchain for Wearable Internet of Things in Healthcare
12. AI-Based Robotics in E-Healthcare Applications
13. Automated Health Monitoring System Using the Internet of Things for Improving Healthcare
14. Biomedical Data Analysis: Current Status and Future Trends
Part 4: Future Research Directions for Intelligent and Automated Healthcare Environment
15. Healthcare 4.0 in Prospective of Respiratory Support System and Artificial Lung
16. Lifestyle Revolution: The Way to Healthcare, Case of India
Part 5: Shifting of Healthcare Systems Toward Emerging Technologies
17. Internet of Things-Based Cloud Applications: Open Issues, Challenges, and Future Research Directions
18. Genomics and Genetic Data: A Third Eye for Doctors
Index