Healthcare Applications of Neuro-Symbolic Artificial Intelligence provides a comprehensive introduction to the field of neuro-symbolic AI, presenting the most recent advances in deep learning and integration of neuro-symbolic (NS) systems and Large Language Models (LLMs). The book evaluates traditional approaches, current approaches, and the author’s own approach to NS in order to create hybrid architectures and reasoning techniques to overcome limitations of most existing AI systems such as deep learning, neural networks, and symbolic AI.
This book will be a welcomed resource for researchers and graduate students in artificial intelligence, natural language processing, and biomedical informatics, as well as professionals in software development who are looking to redesign current systems to leverage LLM through the health application of neuro-symbolic architecture.
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
Height:
Width:
Spine:
Weight:0.00