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Next Generation Computing Techniques for Biomedical Applications

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- Format:
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30 October 2025
The aim of proposed book is to provide researchers and students with a comprehensive understanding of the evolving landscape of Next Generation Computing techniques for Biomedical Applications in digital health over traditional health. A wide, multidisciplinary notion called "digital health" or "digital healthcare" comprises ideas from the point where technology and healthcare converge. Digital health extends digital transformation to the healthcare sector and includes software, hardware, and solutions. The extensive field of digital health, which includes wearable technologies, telehealth and telemedicine, and personalised medicine, as well as mobile health (mHealth) apps and health information technology (IT). Benefits of digital health over traditional healthcare practices are reducing hospital re-admissions, cost savings, enhancing treatment adherence, reduce travel time, increases patient engagement and many more. So, today's healthcare system is becoming more and more dependent on digital technology. The proposed book covers next generation computing techniques for biomedical applications.
This book addresses the different seen and unseen problems which lie within the landscape of Next Generation Computing, and presents an innovative solution to healthcare. The primary focus of the book is to enhance the learning of postgraduate students and research scholars in the research area of next generation computing techniques for biomedical applications.
Key Features:
- To help beginners and professionals in the field gain the most recent advances in healthcare systems
- For industrial and academic researchers
- Outlines the key design issues and future directions for research in next-generation computing for biomedical applications.
- Explains the underlying ideas behind numerous approaches, including artificial intelligence, machine learning, deep learning, etc., with practical applications

MEDICAL / Allied Health Services / Medical Technology, Biomedical engineering, TECHNOLOGY & ENGINEERING / Biomedical, Medical and health informatics

PART1 INTRODUCTION TO COMPUTING TECHNIQUES IN BIOMEDICAL FIELDS
1 Computing Techniques: Advantages, challenges and opportunities
2 Quantum computing in healthcare
3 Computing techniques in medical practices
4 Reconfigurable computing for healthcare application
5 AI ethics in biomedical practices
PART 2 COMPUTING TECHNIQUES IN BIOMEDICAL DATA PROCESSING & SECURITY
6 Artificial Intelligence for Biomedical data analysis and processing
7 Enhancement, segmentation and classification algorithms along with performance metrics for biomedical data processing
8 Big data analytics process to improve healthcare processes
9 Bio-inspired algorithms for biomedical data applications
10 Formation of Secure Biomedical Data Sharing on Cloud Platforms
11 Blockchain technology for secure distributed patient record
12 Case studies: Visual analysis, Prediction and Evaluation of Biomedical data in the context of big data
PART 3 COMPUTING TECHNIQUES IN BIOMEDICAL SIGNAL AND IMAGE PROCESSING
13 AI image recognition and processing technology in Medical Diagnostics
14 Predictive analysis in Medical Imaging
15 AI techniques in Brain signal processing for neural disorders
16 Case studies: Image processing modules for cancer detection & cure
SECTION 4 ARTIFICIAL INTELLIGENCE FOR DISEASE PREDICTION
17 Feature identification and selection for smart healthcare models
18 Intelligent Hyperparameter Optimization AI Model for the detection of Early Disease Diagnostics
19 Involvement with Medical Resources Allocation and Health 4.7 Status based on visual analytics of big data
20 AI Techniques in diagnostic tool for cardiovascular risk prediction
21 Computing Algorithm approach in prediction of Liver Cancer
SECTION 5 VIRTUAL HEALTHCARE APPLICATION & HUMEN COMPUTER INTERFACES
22 Role of virtual assistants for healthcare operations
23 Digital Twin in Healthcare: Advantages, challenges and applications
24 Smart Mobile apps and wearable devices for healthcare
25 Brain computer interfaces (BCI)
26 Case studies: Virtual child care, pregnant women or other patient monitoring systems