A Novel Hybrid AI Framework Combining Machine Learning and Knowledge-Based Systems for Decision Support
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Abstract
The integration of data-driven machine learning models with rule-based knowledge systems has the potential to enhance decision-making across industries. This paper proposes a novel hybrid AI framework that combines deep learning with expert systems to improve interpretability and robustness. The proposed approach is evaluated in the context of medical diagnostics, cybersecurity, and financial risk assessment. Experimental results demonstrate that the hybrid framework outperforms standalone machine learning models in scenarios requiring high precision and domain-specific knowledge.
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References
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