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

Nyhet

Häftad, Engelska, 2025

2 419 kr

Kommande

Generative AI, Large Language Models, Graph Neural Networks and Knowledge Graphs Applications offers readers a thorough examination of the cutting-edge technologies that are shaping the future of artificial intelligence. Through clear explanations and practical insights, this book bridges theoretical concepts and real-world applications, helping professionals, researchers, and academics understand and implement advanced AI solutions. With a focus on the foundational principles of Generative AI, LLMs, GNNs, and Knowledge Graphs, the text emphasizes their collaborative potential and provides guidance for solving complex problems across multiple disciplines.

The book also stands out for its emphasis on hands-on learning, featuring practical examples and case studies from industries such as healthcare and finance. It highlights interdisciplinary applications, demonstrating how these technologies can be leveraged to address real-world challenges. Readers benefit from comprehensive coverage of each topic, deep dives into their interconnections, and actionable strategies for staying at the forefront of AI advancements.

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

Utgivningsdatum2025-11-21
Mått191 x 235 x undefined mm
Vikt450 g
FormatHäftad
SpråkEngelska
SerieArtificial Intelligence Applications in Healthcare and Medicine
Antal sidor500
FörlagElsevier Science
ISBN9780443445972

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Biologi inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och it

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

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