AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Experimental results show that the proposed framework balances recognition performance, computational efficiency, and interpretability, making it ideal for actual emotion-aware intelligent systems.
SHAP (SHapley Additive exPlanations) analysis supports the assertion that the quantity of follicles, FSH/LH ratio, and the level of LH should be considered the most prevalent predictors, and that the evidence provided by the analysis can be interpreted by clinicians and corresponds to the Rotterdam diagnostic criteria.
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