Explainable machine learning for breast mass characterization and malignancy risk stratification: multimodal integration of AI-derived structured digital breast tomosynthesis features and peripheral blood immune-inflammatory biomarkers
Background Accurate discrimination between benign and malignant breast masses is essential for biopsy decisions and individualized management. This study aimed to develop an interpretable machine-learning model integrating artificial intelligence (AI)-structured digital breast tomosynthesis (DBT) mass features with per...
Lu Nie, Yun Wei, Xinyu Feng et al.
· Frontiers in Cell and Develo... · 0 citations