
Artificial Intelligence in Tissue and Organ Regeneration
- 1st Edition - August 18, 2023
- Imprint: Academic Press
- Editors: Chandra P. Sharma, Thomas Chandy, Vinoy Thomas
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 8 4 9 8 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 8 4 9 9 - 4
Artificial Intelligence in Tissue and Organ Regeneration discusses the role of artificial intelligence as a highly sought-after technology in the area of organ and tissue regenerat… Read more

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Request a sales quoteArtificial Intelligence in Tissue and Organ Regeneration discusses the role of artificial intelligence as a highly sought-after technology in the area of organ and tissue regeneration. Certain groups have made significant progress in mass producing mini organs and organoids from stem cells utilizing such techniques. As time goes on, there will be a need to improve these procedures, protocols, regulatory guidelines, and their clinical implications.
- Integrates existing literature in a highly interdisciplinary area
- Presents comprehensive current and future perspectives, combining artificial intelligence and machine learning with organ and tissue regeneration
- Provides new and emerging technology that is useful in healthcare and the medical field
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Preface
- Section 1. Machine learning and artificial intelligence concepts
- Chapter 1. Artificial Intelligence in tissue and organ regeneration: An introduction
- Introduction
- AI in organ regeneration
- Artificial intelligence in healthcare
- Application of AI in tissue engineering
- AI in biomaterials evolution
- Conclusion
- Chapter 2. Introduction to artificial intelligence and machine learning algorithms
- Introduction
- The birth and rise of machine learning
- Branches of artificial intelligence
- Ethical concerns of AI
- Scientific advancement
- Conclusion
- Chapter 3. ML and AI approaches for design of tissue scaffolds
- Introduction
- Collaborative Intelligence: Human centered AI
- AI-aided design strategies for tissue engineering scaffolds
- ML-assisted 2D-printing of tissue engineering scaffolds
- ML-assisted 3D printing of tissue engineering scaffolds
- ML-assisted 4D-printing of tissue engineering scaffolds
- ML and AI-based in vitro imaging of cells on scaffolds
- Challenges of ML in devising scaffold biomaterials
- Future perspective of ML and AI in biomaterials and scaffold manufacturing
- Summary
- Chapter 4. Use of artificial intelligence in assistive devices
- Introduction
- Discussion
- Conclusion
- Section 2. AI applications in organ regeneration
- Chapter 5. Applying Artificial Intelligence in solid organ failure, organ transplant selection, preservation, and regeneration
- Key point
- Background
- Solid organ failure
- Conclusion and future directions
- Chapter 6. AI in angiogenesis: moving towards designer vasculature
- Introduction
- Overview of vasculature system
- Synthesis of blood vessel
- Overview of the widely used AIML models in tissue engineering
- AI in analyzing vasculature
- AI in designing microvasculature
- Conclusion and future scope
- Chapter 7. Prospects of artificial intelligence in regeneration and repair of organs
- Introduction
- Roadblocks in the clinical realization of organ regeneration therapies
- Prospects of ML and AI techniques in organ regeneration approaches
- Future perspectives
- Conclusions
- Chapter 8. AI on DDS for regenerative medicine
- Introduction
- Drug delivery materials
- Role of drug delivery systems in regenerative medicine
- Artificial intelligence (AI) in designing of drug delivery systems
- AI in regenerative medicine
- Conclusion and future perspective
- Chapter 9. Optimization of bio-ink using machine learning
- Introduction
- Physiochemical requirements
- Introduction to machine learning
- Machine learning techniques for the optimization of bio-ink
- Conclusion
- Chapter 10. Artificial intelligence in stem cell therapies and organ regeneration
- What is the regenerative healing process?
- Role of stem cell therapy in the regenerative healing process
- Role of artificial intelligence in stem cell therapy
- Implementation of various AI techniques in stem cell therapy
- Role of artificial intelligence in organ regeneration
- Future perspectives and challenges of AI in stem cell therapy
- Conclusion
- Section 3. AI applications and bio-manufacturing
- Chapter 11. Artificial intelligence in multiscale scaffolds for cancer organoids testbed
- Introduction
- AI in scaffold design
- Cancer organoids research using AI-based technologies
- Future directions
- Chapter 12. Complex data representation, modeling and computational power for a personalized dialysis
- Background
- Systems biology and network biology for the personalization of dialysis
- Data-driven machine learning-based analysis
- Development of Novel architecture computational models and future trends
- Technological requirements for a personalized dialysis, initiatives to stimulate innovations and future directions
- Summary and bullet points
- Some equations, algorithms and basic maths for ML
- Chapter 13. Neural encoding of artificial sensations evoked by peripheral nerve stimulation for neuroprosthetic applications
- Invasive neurostimulation approaches
- Noninvasive neurostimulation approaches
- Somatosensory information encoding
- AI toward personalized neuroprostheses
- Future perspectives
- Chapter 14. Applying AI to advanced biomanufacturing
- Introduction
- Current state of the field in biomanufacturing: Actual and potential
- Broadening the application of AI early and often in advanced biomanufacturing: A collaborative testbed model for integrating AI into small-scale operations and early phase trials
- Conclusions
- Chapter 15. Regulatory pathways for ML and AI devices
- Introduction to artificial intelligence and machine learning regulation
- Is my product a medical device?
- Software in a medical device (SiMD)
- Software as a medical device (SaMD)
- Commercial off-the-shelf software
- Defining your intended purpose
- Impact of machine learning/artificial intelligence
- Classification
- United States classification
- European Union
- Other regulatory regions
- Creating a regulatory strategy
- Software specific considerations
- Removing bias in data algorithms
- Cybersecurity
- NB engagement
- Technical documentation creation
- Design controls
- Clinical data
- Analyzing post market data
- Conclusion
- Chapter 16. AI and ML: challenges and future perspective in artificial organs realm
- Introduction
- Conclusions
- Index
- Edition: 1
- Published: August 18, 2023
- Imprint: Academic Press
- No. of pages: 342
- Language: English
- Paperback ISBN: 9780443184987
- eBook ISBN: 9780443184994
CS
Chandra P. Sharma
TC
Thomas Chandy
VT
Vinoy Thomas
Dr. Vinoy Thomas is an Associate Professor and Graduate Program Director in the Department of Mechanical and Materials Engineering at the University of Alabama at Birmingham. He also holds secondary appointments at the Department of Biomedical Engineering, Department of Physics and Department of Environmental Science & Health. Dr. Thomas is also an Associate Scientist at the Center for Nanoscale Materials and Biointegration (CNMB) and Center for Clinical and Translational Sciences (CCTS). After his PhD in Biomaterials & Technology, he completed postdoctoral training at Friedrich-Schiller University (FSU), Jena, Germany, and at the National Institute of Standards & Technology (NIST), Gaithersburg, USA. His research focuses on biomaterials processing-property relationships, nanomaterials for tissue engineering and drug delivery . He has published over 120 scientific research and review articles (h- index: 36), co-edited two books (Tissue Engineering, Elsevier 2022 and Artificial Intelligence in Tissue and Organ Regeneration, Elsevier 2023). He serves as Associate Editor of Heliyon (Engineering). Dr. Thomas received Fellow Awards such as FBAO -from Society for Biomaterials and Artificial Organs India, FAAS- from Alabama Academy of Sciences, and IAAM Scientist Medal from International Association of Advanced Materials, Sweden. Dr. Thomas is currently serving as the President of Alabama Academy of Science (AAS), Chairman of SBAOI- North American Chapter, and Secretary of Biomaterials Committee of The Minerals, Metals, and Materials Society (TMS).