Computational Intelligence in Bioprinting
Challenges and Future Directions
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Computational Intelligence in Bioprinting
Challenges and Future Directions
About this book
COMPUTATIONAL INTELLIGENCE IN BIOPRINTING
The book provides a comprehensive exploration of the evolving field of bioprinting in regenerative medicine and is an essential guide for professionals seeking a thorough understanding of the field.
Computational Intelligence in Bioprinting provides a comprehensive overview of the evolving field of bioprinting in reformative medicine, defining the process of printing structures using viable cells, biomaterials, and living molecules. The primary goal is to provide substitutes for tissue implants, which might lead to eliminating the requirement for organ donors, as well as to transform animal testing for the learning and analysis of disease and the growth of treatments. The book offers a comprehensive overview of bioprinting technologies and their applications, emphasizing the integration of computation intelligence, artificial intelligence, and other computer science advancements in the field. By harnessing the power of computational intelligence techniques such as AI, machine learning, optimization algorithms, and data analytics, existing hurdles can be overcome and the full potential of bioprinting can be unlocked.
The book covers an extensive range of topics, including bio-ink formulation and characterization, bioprinter hardware and software design, tissue and organ modeling, image analysis, process optimization, and quality control.
Audience
The book is aimed at professionals, practitioners and researchers in the fields of bioprinting, tissue engineering, and computational intelligence in medicine.
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Information
Table of contents
- Cover
- Table of Contents
- Series Page
- Title Page
- Copyright Page
- Preface
- 1 The Emergence of Bioprinting and Computational Intelligence
- 2 Design, Architecture, Implementation, and Evaluation of Bioprinting Technology for Tissue Engineering
- 3 Design and Development of IoT Devices: Methods, Tools and Technologies
- 4 AI-Based AR/VR Models in Biomedical Sustainable Industry 4.0
- 5 Computational IntelligenceāBased Image Classification for 3D Printing: Issues and Challenges
- 6 Role of Cybersecurity to Safeguard 3D Bioprinting in Healthcare: Challenges and Opportunities
- 7 Legal and Bioethical View of Educational Sectors and Industrial Areas of 3D Bioprinting
- 8 Optimizing 3D Bioprinting Using Advanced Deep Learning Techniques A Comparative Study of CNN, RNN, and GAN
- 9 Research Trends in IntelligenceāBased Bioprinting for Construction Engineering Applications
- 10 Design and Development to Collect and Analyze Data Using Bioprinting Software for Biotechnology Industry
- 11 Cyborg Intelligence for Bioprinting in Computational Design and Analysis of Medical Application
- 12 Computer Vision-Aides 3D Bioprinting in Ophthalmology Recent Trends and Advancements
- 13 Intelligent Image Classification for 3D Printing in Industry 4.0
- 14 Bioprinting and Robotics Engineering: Applications, Recent Progress, and Future Directions
- 15 3D Bioprinting Technology Optimization Using Machine Learning
- Index
- End User License Agreement