Multimodal Data Fusion for Bioinformatics Artificial Intelligence
eBook - PDF

Multimodal Data Fusion for Bioinformatics Artificial Intelligence

  1. 406 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Multimodal Data Fusion for Bioinformatics Artificial Intelligence

About this book

Multimodal Data Fusion for Bioinformatics Artificial Intelligence is a must-have for anyone interested in the intersection of AI and bioinformatics, as it delves into innovative data fusion methods and their applications in 'omics' research while addressing the ethical implications and future developments shaping the field today.

Multimodal Data Fusion for Bioinformatics Artificial Intelligence is an indispensable resource for those exploring how cutting-edge data fusion methods interact with the rapidly developing field of bioinformatics. Beginning with the basics of integrating different data types, this book delves into the use of AI for processing and understanding complex "omics" data, ranging from genomics to metabolomics. The revolutionary potential of AI techniques in bioinformatics is thoroughly explored, including the use of neural networks, graph-based algorithms, single-cell RNA sequencing, and other cutting-edge topics.

The second half of the book focuses on the ethical and practical implications of using AI in bioinformatics. The tangible benefits of these technologies in healthcare and research are highlighted in chapters devoted to precision medicine, drug development, and biomedical literature.

The book addresses a wide range of ethical concerns, from data privacy to model interpretability, providing readers with a well-rounded education on the subject. Finally, the book explores forward-looking developments such as quantum computing and augmented reality in bioinformatics AI. This comprehensive resource offers a bird's-eye view of the intersection of AI, data fusion, and bioinformatics, catering to readers of all experience levels.

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Yes, you can access Multimodal Data Fusion for Bioinformatics Artificial Intelligence by Umesh Kumar Lilhore,Abhishek Kumar,Narayan Vyas,Sarita Simaiya,Vishal Dutt in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Series Page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Preface
  7. Chapter 1 Advancements and Challenges in Multimodal Data Fusion for Bioinformatics AI
  8. Chapter 2 Automated Machine Learning in Bioinformatics
  9. Chapter 3 Data-Driven Discoveries: Unveiling Insights with Automated Methods
  10. Chapter 4 Comparative Analysis of Conventional Machine Learning and Deep Learning Techniques for Predicting Parkinson’s Disease
  11. Chapter 5 Foundations of Multimodal Data Fusion
  12. Chapter 6 Integrating IoT, Blockchain, and Quantum Machine Learning: Advancing Multimodal Data Fusion in Healthcare AI
  13. Chapter 7 Integrating Multimodal Data Fusion for Advanced Biomedical Analysis: A Comprehensive Review
  14. Chapter 8 Machine Learning Approaches for Integrating Imaging and Molecular Data in Bioinformatics
  15. Chapter 9 Time Series Analysis in Functional Genomics
  16. Chapter 10 Review of Multimodal Data Fusion in Machine Learning: Methods, Challenges, Opportunities
  17. Chapter 11 Recent Advancement in Bioinformatics: An In-Depth Analysis of AI Techniques
  18. Chapter 12 Future Directions and Emerging Trends in Multimodal Data Fusion for Bioinformatics
  19. Chapter 13 Future Trends in Bioinformatics AI Integration
  20. Chapter 14 Emerging Technologies in IoM: AI, Blockchain and Beyond
  21. Chapter 15 Natural Language Processing in Biomedical Literature
  22. Chapter 16 Biomedical Research Enrichment Through Sentiment Analysis in Patient Feedback: A Natural Language Processing Approach
  23. About the Editors
  24. Index
  25. Also of Interest
  26. EULA