Article Versions Notes

Guldogan E, Yagin FH, Ucuzal H, Alzakari SA, Alhussan AA, Ardigò LP. Interpretable Machine Learning for Serum-Based Metabolomics in Breast Cancer Diagnostics: Insights from Multi-Objective Feature Selection-Driven LightGBM-SHAP Models. Medicina. 2025; 61(6):1112. https://doi.org/10.3390/medicina61061112

Guldogan, Emek, Fatma Hilal Yagin, Hasan Ucuzal, Sarah A. Alzakari, Amel Ali Alhussan, and Luca Paolo Ardigò. 2025. "Interpretable Machine Learning for Serum-Based Metabolomics in Breast Cancer Diagnostics: Insights from Multi-Objective Feature Selection-Driven LightGBM-SHAP Models" Medicina 61, no. 6: 1112. https://doi.org/10.3390/medicina61061112

Guldogan, E., Yagin, F. H., Ucuzal, H., Alzakari, S. A., Alhussan, A. A., & Ardigò, L. P. (2025). Interpretable Machine Learning for Serum-Based Metabolomics in Breast Cancer Diagnostics: Insights from Multi-Objective Feature Selection-Driven LightGBM-SHAP Models. Medicina, 61(6), 1112. https://doi.org/10.3390/medicina61061112