Generative AI, Large Language Models, Graph Neural Networks and Knowledge Graphs Applications
- 1st Edition - November 21, 2025
- Editor: Abdulhamit Subasi
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 4 4 5 9 7 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 4 4 5 9 8 - 9
Generative AI, Large Language Models, Graph Neural Networks, and Knowledge Graphs Applications provides a comprehensive exploration of transformative technologies reshaping artifi… Read more
Generative AI, Large Language Models, Graph Neural Networks, and Knowledge Graphs Applications provides a comprehensive exploration of transformative technologies reshaping artificial intelligence. This 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. The content covers 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, it illustrates their applications across diverse fields such as healthcare and finance, making complex concepts accessible and actionable. For academics, researchers, and industry professionals, this book offers invaluable insights and practical guidance. By emphasizing hands-on learning and clear explanations, it equips readers with the knowledge and skills necessary to navigate and implement cutting-edge AI technologies, 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, from foundational concepts to 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 seeking to deepen their knowledge due to breaking down complex topics into easy-to-understand language
Undergraduate and graduate students studying artificial intelligence, data science, computer science, and related fields.as well as researchers in academia and industry
PART I: Key Technologies and Methodologies
1. Deep Learning and Neural Networks
2. Generative Models in Depth
3. Transformers and Attention Mechanisms
4. Understanding Large Language Models (LLMs)
5. Graph Neural Networks (GNNs) and Knowledge Graphs
6. Combining Generative AI and Large Language Models
7. Enhancing Knowledge Graphs with Generative AI
8. Graph Neural Networks for Knowledge Representation
9. AI-Powered Multimodal Systems: Combining Text, Graphs, and Images
PART II: Practical Applications and Case Studies in Healthcare
10. Alzheimer's Disease detection using KG, GNN and LLMs
11. Schizophrenia detection using KG, GNN and LLMs
12. Bipolar Disorder detection using KG, GNN and LLMs
13. Depression detection using KG, GNN and LLMs
14. Diabetes detection using KG, GNN and LLMs
15. Obesity detection using KG, GNN and LLMs
16. Coronary Artery Disease detection using KG, GNN and LLMs
17. Hypertension detection using KG, GNN and LLMs
18. Rheumatoid Arthritis detection using KG, GNN and LLMs
19. Systemic Lupus Erythematosus detection using KG, GNN and LLMs
20. Breast Cancer detection using KG, GNN and LLMs
21. Prostate Cancer detection using KG, GNN and LLMs
22. Colorectal Cancer detection using KG, GNN and LLMs
23. Parkinson's Disease detection using KG, GNN and LLMs
24. Amyotrophic Lateral Sclerosis detection using KG, GNN and LLMs
25. scRNA analysis using KG, GNN and LLMs
26. Social Media Text as a Tool for Monitoring Public Mental Health Trends: A Sentiment Analysis
PART III: Practical Applications and Case Studies in Cybersecurity
27. Malware Analysis using KG, GNN and LLMs
28. DDoS attack dataset against EV authentication using KG and GNN
29. Attack detection in Internet of Medical Things using KG and GNN
30. IDS in Internet of Vehicles (IoV) using KGs and GNN
31. EV charger attack detection using KG and GNN
32. Automatic Reasoning for Fact Verification Using KGs and Language Models
33. Attack detection in IoT environment using KGs and LLMs
34. Modbus attack detection using KG and GNN
35. LLM-based models to assess the accuracy of real/fake tweet detection
1. Deep Learning and Neural Networks
2. Generative Models in Depth
3. Transformers and Attention Mechanisms
4. Understanding Large Language Models (LLMs)
5. Graph Neural Networks (GNNs) and Knowledge Graphs
6. Combining Generative AI and Large Language Models
7. Enhancing Knowledge Graphs with Generative AI
8. Graph Neural Networks for Knowledge Representation
9. AI-Powered Multimodal Systems: Combining Text, Graphs, and Images
PART II: Practical Applications and Case Studies in Healthcare
10. Alzheimer's Disease detection using KG, GNN and LLMs
11. Schizophrenia detection using KG, GNN and LLMs
12. Bipolar Disorder detection using KG, GNN and LLMs
13. Depression detection using KG, GNN and LLMs
14. Diabetes detection using KG, GNN and LLMs
15. Obesity detection using KG, GNN and LLMs
16. Coronary Artery Disease detection using KG, GNN and LLMs
17. Hypertension detection using KG, GNN and LLMs
18. Rheumatoid Arthritis detection using KG, GNN and LLMs
19. Systemic Lupus Erythematosus detection using KG, GNN and LLMs
20. Breast Cancer detection using KG, GNN and LLMs
21. Prostate Cancer detection using KG, GNN and LLMs
22. Colorectal Cancer detection using KG, GNN and LLMs
23. Parkinson's Disease detection using KG, GNN and LLMs
24. Amyotrophic Lateral Sclerosis detection using KG, GNN and LLMs
25. scRNA analysis using KG, GNN and LLMs
26. Social Media Text as a Tool for Monitoring Public Mental Health Trends: A Sentiment Analysis
PART III: Practical Applications and Case Studies in Cybersecurity
27. Malware Analysis using KG, GNN and LLMs
28. DDoS attack dataset against EV authentication using KG and GNN
29. Attack detection in Internet of Medical Things using KG and GNN
30. IDS in Internet of Vehicles (IoV) using KGs and GNN
31. EV charger attack detection using KG and GNN
32. Automatic Reasoning for Fact Verification Using KGs and Language Models
33. Attack detection in IoT environment using KGs and LLMs
34. Modbus attack detection using KG and GNN
35. LLM-based models to assess the accuracy of real/fake tweet detection
- Edition: 1
- Published: November 21, 2025
- Language: English
AS
Abdulhamit Subasi
Abdulhamit Subasi is a highly specialized expert in the fields of Artificial Intelligence, Machine Learning, and Biomedical Signal and Image Processing. 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. His career has spanned various prestigious institutions, including the Georgia Institute of Technology in Georgia, USA, where he served as a dedicated researcher. In recognition of his outstanding research contributions, Subasi received the prestigious Queen Effat Award for Excellence in Research in May 2018. His academic journey includes a tenure as a Professor of computer science at Effat University in Jeddah, Saudi Arabia, from 2015 to 2020. Since 2020, he has assumed the role of Professor of medical physics at the Faculty of Medicine, University of Turku in Turku, Finland
Affiliations and expertise
Institute of Biomedicine, Faculty of Medicine, University of Turku, Turku, Finland Department of Computer Science, College of Engineering, Effat University, Jeddah, Saudi Arabia