Researchers from Pusan National University have developed an advanced machine learning approach called Feature Localized Intercept Transformed-Shapley Additive Explanations (FLIT-SHAP) to analyze complex pollutant interactions. This method reveals hidden synergistic and antagonistic effects among pollutants, providing accurate toxicity predictions (R² = 0.99). The approach highlights the significant impact of chemicals like quinones on toxicity, suggesting improved regulatory strategies for environmental health risks.
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