1st Edition
Intelligent Interactive Multimedia Systems for e-Healthcare Applications
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.
PART 1: INTRODUCTION OF MULTIMEDIA IN HEALTHCARE APPLICATIONS
1. Data Visualization for Healthcare
S. Usharani, P. Manju Bala, R. Rajmohan, T. Ananth Kumar, and M. Pavithra
2. Health Monitoring and Management System Using Machine Learning Techniques
Bharati Patil and Vydeki D.
3. A Study on Fusion Methods and Their Applications in Medical Image Processing
P. Nischitha and Chandra Singh
4. A Study on an Elderly Caretaker Bot Using Computer Vision and Artificial Intelligence
Chandra Singh, P. Nischitha, Ashwath Rao, Shailesh S. Shetty, and Pavanalaxmi
5. Knowledge Shift for Candidate Categorization in Lung Nodule Detection Using 3D Convolutional Neural Network
P. Manju Bala, S. Usharani, R. Rajmohan, M. Pavithra, and T. Ananth Kumar
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
Sachin Kamley
7. Mathematical Model of COVID-19 Diagnosis Prediction Using Machine Learning Techniques
V. Kakulapati and M. Nagaraju
8. Detection and Classification of Knee Osteoarthritis Using Texture Descriptor Algorithms
Anjani Hegde, Rishma Mary George, and H. D. Ranjith
9. Sensor Cloud-Based Theoretical Machine Learning Models for Predicting Pandemic Diseases
Prashant Sangulagi and Ashok V Sutagundar
PART 3: APPLICATIONS FOR INTELLIGENT AND AUTOMATED HEALTHCARE SYSTEMS
10. Applications of Machine Learning Algorithms in Fetal ECG Enhancement for E-Healthcare
Yojana Sharma, Shashwati Ray, and Om Prakash Yadav
11. Blockchain for Wearable Internet of Things in Healthcare
Shubhangi Kharche and Rizwana Shaikh
12. AI-Based Robotics in E-Healthcare Applications
P. Praveen Kumar, T. Ananth Kumar, R. Rajmohan, and M. Pavithra
13. Automated Health Monitoring System Using the Internet of Things for Improving Healthcare
Vergin Raja Sarobin M., Sherly Alphonse, and Jani Anbarasi L.
14. Biomedical Data Analysis: Current Status and Future Trends
Amit Kumar Tyagi, S. U. Aswathy, and Shaveta Malik
PART 4: FUTURE RESEARCH DIRECTIONS FOR INTELLIGENT AND AUTOMATED HEALTHCARE ENVIRONMENT
15. Healthcare 4.0 in Prospective of Respiratory Support System and Artificial Lung
Moupali Roy, Arpan Das, Biswarup Neogi, and Prabir Saha
16. Lifestyle Revolution: The Way to Health Care, Case of India
Raju K. Kurian, Jyotsna Haran, and Saurabh Ojha
PART 5: SHIFTING OF HEALTHCARE SYSTEMS TOWARD EMERGING TECHNOLOGIES
17. Internet of Things-Based Cloud Applications: Open Issues, Challenges, and Future Research Directions
Siddharth M. Nair, R. Varsha, Amit Kumar Tyagi, and S. U. Aswathy
18. Genomics and Genetic Data: A Third Eye for Doctors
M. Shamila, Amit Kumar Tyagi, and S. U. Aswathy
Biography
Shaveta Malik, PhD, is Associate Professor in the Computer Engineering Department at Terna Engineering College, University of Mumbai, Nerul, India. She has more than 11 years of teaching and research experience. She is a member of numerous editorial boards and scientific and advisory committees of international conferences and journals. She has been a co-chair at international conferences also. Her research area focuses on image processing, machine learning, deep learning, and artificial intelligence.
Amit Kumar Tyagi, PhD, is Assistant Professor (Senior Grade) and Senior Researcher at Vellore Institute of Technology, Chennai Campus, India. His current research focuses on machine learning with big data, blockchain technology, data science, cyber-physical systems, smart computing, and security and privacy. He has contributed to several projects such as AARIN and P3-Block to address some of the open issues related to privacy breaches in vehicular applications (such as parking) and medical cyber-physical systems. He is a member of IEEE.
