Artificial Intelligence and Blockchain in Precision Medicine and Virology

The book stands at the intersection of medical virology, computer science engineering, and artificial intelligence. This interdisciplinary book seeks to harness the strengths of these fields to address the complex challenges of diagnosing, treating, and managing viral diseases. Medical virology, which studies viruses and virus-like agents, plays a critical role in understanding infectious diseases and developing therapeutic strategies. However, the field faces immense challenges due to the sheer volume and complexity of virological data, which demands advanced computational tools for effective analysis and application.
Computer science engineering provides the technological backbone for this initiative. Engineers in this field develop and implement sophisticated algorithms and data structures that enable the processing of large-scale virological datasets. In this context, computer science engineering is pivotal for creating the infrastructure necessary for deep learning and blockchain technologies. Deep learning, a branch of artificial intelligence, involves training neural networks to recognize patterns in vast datasets, enabling the discovery of insights that are otherwise obscured. When applied to medical virology, deep learning can significantly enhance the accuracy of viral diagnostics, predict disease outbreaks, and personalize treatment regimens based on the genetic makeup of both viruses and patients

List of contents

Part 1. Fundamentals of AI and Deep Learning in Healthcare.- Chapter 1.    Artificial Intelligence and Deep Learning in Healthcare.- Chapter 2. Human-Centric Artificial Intelligence (HCAI) for Precision Clinical and Medical Virology.- Chapter 3. Deep Learning Algorithms and Techniques.- Chapter 4. Applications of Deep Learning in Virology.- Part 2. AI and Blockchain Applications in Medical Virology.- Chapter 5.    Deep Learning in Viral Diagnosis: Case Studies and Emerging Frameworks for Precision Medical Virology.- Chapter 6. Implementing Machine Learning for Analyzing Influenza A Virus with Hemagglutinin Sequences.- Chapter 7. Transforming Global Health: The Impact of AI and Blockchain on Viral Disease Control.- Chapter 8. A blockchain-based trust architecture for securing pandemic test results in decentralized health networks.- Chapter 9. Building Trust through AI: AI Approaches to Medical Virology in Future Healthcare Systems.- Chapter 10. Integrating Federated Deep Learning and Blockchain for Privacy-Preserving Precision Medicine in Medical Virology.- Chapter 11. Integrating Deep Convolutional Neural Network with Blockchain for Secure and Transparent Data Management in Decentralized Healthcare Systems.- Chapter 12. Case Studies: Blockchain in Medical Virology.- Part 3. Advanced AI for Disease Prediction and Medical Innovations.- Chapter 13. Bio-Inspired Approaches for Optimal Kidney Paired Donation (Infectious Risk Analysis).- Chapter 14. Anemia Prediction Based on Eye Condition Data.- Chapter 15. AI for Multi-Region Tumour Detection: Enhancing Human Workflow in Full-Body Scans.- Chapter 16. Enhancing classification accuracy in virology through deep learning for accurate virus identification from tem imagery.- Chapter 17. Advancing prognostic insights:  a novel deep learning algorithm to predict outcomes in amyotrophic lateral sclerosis.- Chapter 18. Cultivating Innovative AI Paradigms for Enriching Patient Engagement and Elevating Telehealth Services.- Chapter 19. Ethical and legal considerations in leveraging ai and blockchain for equitable healthcare access for disabled populations.- Chapter 20. Analysing the Impact & Challenges of Deep Learning Models in Virology.

About the author

Jyotir Moy Chatterjee currently holds a position as an Assistant Professor in the Department of Computer Science and Engineering (CSE) at Graphic Era Deemed to be University, located in Dehradun, Uttarakhand, India. He also serves as a Visiting Faculty Assistant Professor in the Department of Information Technology (IT) at Lord Buddha Education Foundation in Kathmandu, Nepal, affiliated with Asia Pacific University, Malaysia. Prior to these engagements, he fulfilled roles as an Assistant Professor and Program Leader for the Bachelor of Science in Information Technology (B.Sc. IT) program at Lord Buddha Education Foundation and as Assistant Professor in the CSE Department at GD-Rungta College of Engineering & Technology, affiliated with Chhattisgarh Swami Vivekananda Technical University in Bhilai, India. His academic qualifications include a Master of Technology (M.Tech) in Computer Science and Engineering from Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, obtained in 2016, and a Bachelor of Technology (B.Tech) in Computer Science and Engineering from Dr. MGR Educational & Research Institute, Maduravoyal, Chennai, acquired in 2013. His research interests are primarily concentrated on machine learning and deep learning.
Professor (Dr.) Shailendra K. Saxena holds the position of Vice Dean and Professor at King George's Medical University, Lucknow, India. His research is centered on elucidating the molecular mechanisms of host defense mechanisms during human viral infections and developing novel predictive, preventive, and therapeutic strategies, utilizing both emerging and re-emerging viruses as models through stem cell and cell culture technologies. His scholarly work is extensively published in high-impact journals such as Science, Proceedings of the National Academy of Sciences (PNAS), and Nature Medicine, attracting significant citations. He has received numerous prestigious awards and honors both in India and internationally, including several Young Scientist Awards, the Biotechnology and Biological Sciences Research Council (BBSRC) India Partnering Award from the UK, the Dr. JC Bose National Award from the Department of Biotechnology, Ministry of Science and Technology, Government of India, and fellowships with various eminent bodies such as The Royal College of Pathologists (UK), the Royal Societies of Biology and Chemistry, London, UK, the Academy of Translational Medicine Professionals, Austria, and the Indian Virological Society. Recognized as the "Global Leader in Science" by The Scientist magazine (USA), he is also acknowledged as an International Opinion Leader/Expert on vaccination for Japanese Encephalitis (JE) by the Immunisation Practice Improvement Consortium (IPIC, UK). His inclusion in the "World’s Top 2% Scientists" list by Stanford University, California, USA, highlights his significant contributions to global research.

Summary

The book stands at the intersection of medical virology, computer science engineering, and artificial intelligence. This interdisciplinary book seeks to harness the strengths of these fields to address the complex challenges of diagnosing, treating, and managing viral diseases. Medical virology, which studies viruses and virus-like agents, plays a critical role in understanding infectious diseases and developing therapeutic strategies. However, the field faces immense challenges due to the sheer volume and complexity of virological data, which demands advanced computational tools for effective analysis and application.
Computer science engineering provides the technological backbone for this initiative. Engineers in this field develop and implement sophisticated algorithms and data structures that enable the processing of large-scale virological datasets. In this context, computer science engineering is pivotal for creating the infrastructure necessary for deep learning and blockchain technologies. Deep learning, a branch of artificial intelligence, involves training neural networks to recognize patterns in vast datasets, enabling the discovery of insights that are otherwise obscured. When applied to medical virology, deep learning can significantly enhance the accuracy of viral diagnostics, predict disease outbreaks, and personalize treatment regimens based on the genetic makeup of both viruses and patients

Product details

• Assisted by: Jyotir Moy Chatterjee (Editor), K Saxena (Editor), Jyotir Moy Chatterjee (Editor), Shailendra K Saxena (Editor), Shailendra K. Saxena (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Release: 04.09.2025
• EAN: 9789819689187
• ISBN: 978-981-9689-18-7
• No. of pages: 480
• Illustrations: VI, 480 p. 108 illus., 94 illus. in color.
• Series: Medical Virology: From Pathogenesis to Disease Control
• Subject: Natural sciences, medicine, IT, technology > Biology > General, dictionaries