Generative AI, Large Language Models, Graph Neural Networks and Knowledge Graphs Applications

Nyhet

Häftad, Engelska, 2026

2 419 kr

Kommande

Generative AI, Large Language Models, Graph Neural Networks, and Knowledge Graphs Applications provides a comprehensive exploration of the transformative technologies reshaping artificial intelligence. The book bridges the gap between advanced AI concepts and their real-world applications, offering readers a robust understanding of how these technologies can solve complex, interdisciplinary problems. Sections cover the foundational principles of Generative AI, LLMs, GNNs, and Knowledge Graphs, highlighting their interconnections and collaborative potential. Through practical examples and real-world case studies, the book illustrates their applications across diverse fields such as healthcare and finance, making complex concepts accessible and actionable.

For academics, researchers, and industry professionals, it offers invaluable insights and practical guidance. By emphasizing hands-on learning and clear explanations, users will find the knowledge and skills necessary to navigate and implement cutting-edge AI technologies, thus ensuring they remain at the forefront of this rapidly evolving field.

Provides a thorough examination of Generative AI, Large Language Models, Graph Neural Networks, and Knowledge Graphs, including foundational concepts and advanced applications across various fields
Includes practical examples and real-world case studies, allowing readers to directly implement the technologies discussed and bridge the gap between theory and application
Provides accessible content for both newcomers in AI and experienced professionals

Produktinformation

Utgivningsdatum2026-04-24
Mått191 x 235 x undefined mm
Vikt450 g
FormatHäftad
SpråkEngelska
SerieArtificial Intelligence Applications in Healthcare and Medicine
Antal sidor632
FörlagElsevier Science
ISBN9780443445972

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Abdulhamit Subasi is a highly specialized expert in the fields of Artificial Intelligence, Machine Learning, and Biomedical Signal and Image Analysis and Security. His extensive expertise in applying machine learning across diverse domains is evident in his numerous contributions, including the authorship of multiple book chapters, as well as the publication of a substantial body of research in esteemed journals and conferences.

PART I: Key Technologies and Methodologies1. Deep Learning and Neural Networks2. Generative Models in Depth3. Transformers and Attention Mechanisms4. Understanding Large Language Models (LLMs)5. Graph Neural Networks (GNNs) and Knowledge Graphs6. Combining Generative AI and Large Language Models7. Enhancing Knowledge Graphs with Generative AI8. Graph Neural Networks for Knowledge Representation9. AI-Powered Multimodal Systems: Combining Text, Graphs, and ImagesPART II: Practical Applications and Case Studies in Healthcare10. Alzheimer's Disease detection using KG, GNN and LLMs11. Schizophrenia detection using KG, GNN and LLMs12. Bipolar Disorder detection using KG, GNN and LLMs13. Depression detection using KG, GNN and LLMs14. Diabetes detection using KG, GNN and LLMs15. Obesity detection using KG, GNN and LLMs16. Coronary Artery Disease detection using KG, GNN and LLMs17. Hypertension detection using KG, GNN and LLMs18. Rheumatoid Arthritis detection using KG, GNN and LLMs19. Systemic Lupus Erythematosus detection using KG, GNN and LLMs20. Breast Cancer detection using KG, GNN and LLMs21. Prostate Cancer detection using KG, GNN and LLMs22. Colorectal Cancer detection using KG, GNN and LLMs23. Parkinson's Disease detection using KG, GNN and LLMs24. Amyotrophic Lateral Sclerosis detection using KG, GNN and LLMs25. scRNA analysis using KG, GNN and LLMs26. Social Media Text as a Tool for Monitoring Public Mental Health Trends: A Sentiment AnalysisPART III: Practical Applications and Case Studies in Cybersecurity27. Malware Analysis using KG, GNN and LLMs28. DDoS attack dataset against EV authentication using KG and GNN29. Attack detection in Internet of Medical Things using KG and GNN30. IDS in Internet of Vehicles (IoV) using KGs and GNN31. EV charger attack detection using KG and GNN32. Automatic Reasoning for Fact Verification Using KGs and Language Models33. Attack detection in IoT environment using KGs and LLMs34. Modbus attack detection using KG and GNN35. LLM-based models to assess the accuracy of real/fake tweet detection