Buch, Englisch, 300 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g
Buch, Englisch, 300 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g
ISBN: 978-0-443-30046-2
Verlag: Elsevier Science
Healthcare Applications of Neuro-Symbolic Artificial Intelligence provides a comprehensive introduction to the field of neuro-symbolic (NS) artificial intelligence (AI), presenting the most recent advances in deep learning and integration of NS systems and large language models (LLMs). This book evaluates traditional approaches, current approaches, as well as the author’s own approach to NS, to create hybrid architectures and reasoning techniques to overcome the limitations of most existing AI systems such as deep learning, neural networks, and symbolic AI.
This book will be a welcome resource for researchers and graduate students in AI, natural language processing, and biomedical informatics, as well as professionals in software development looking to redesign current systems to leverage LLMs through the health application of NS architecture.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1. Neuro-Symbolic Shaped-Charge Learning Architecture
2. Health Applications of Shaped-Charge Learning
3. Enabling LLM with plug-and-play symbolic reasoning components
4. Extending LLM capabilities beyond reasoning (Boris Galitsky and Alexander Rybalov)
5. Differential Diagnose-making with LLM and Probabilistic Logic Program
6. LLM-based Personalized Recommendations in Health
7. Leveraging Medical Discourse to Answer Complex Questions
8. Identifying LLM Hallucinations in Health Communication
9. Enabling LLMs with explainability
10. Explainability Discourse
11. Enabling Retrieval-Augmented Generation and Knowledge Graphs with Discourse Analysis
12. Employing LLM to solve Constraint Satisfaction
13. Kolmogorov-Arnold Network for Word-Level Explainable Meaning Representation
14. Conclusions
