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    Healthcare Applications of Neuro-Symbolic Artificial Intelligence

    Healthcare Applications of Neuro-Symbolic Artificial Intelligence by Galitsky, Boris;

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      • Publisher's listprice EUR 167.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        71 261 Ft (67 867 Ft + 5% VAT)
      • Discount 20% (cc. 14 252 Ft off)
      • Discounted price 57 008 Ft (54 294 Ft + 5% VAT)

    71 261 Ft

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    Product details:

    • Publisher Academic Press
    • Date of Publication 1 August 2025

    • ISBN 9780443300462
    • Binding Paperback
    • No. of pages300 pages
    • Size 234x190 mm
    • Weight 450 g
    • Language English
    • 700

    Categories

    Long description:

    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.

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    Table of Contents:

    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

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