AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Molecular evaluation of residual disease following neoadjuvant chemotherapy in triple-negative breast cancer CALGB 40603 (Alliance)
BACKGROUND Despite therapeutic advances in early-stage triple-negative breast cancer (TNBC), residual disease (RD) following neoadjuvant therapy remains a key predictor of a worse prognosis and obstacle to improving patient outcomes. METHODS To better characterize RD and identify survival-associated features, we perfor...
Transcriptomic Profiling of Mouse Mammary Tumors Enables Prognostic and Predictive Biomarker Discovery for Human Breast Cancer.
Comparing of multiple computational approaches, including XGBoost, random forests, and support vector regression, showed that all methods successfully predicted survival outcomes, with Elastic Net offering the best performance and interpretability.