A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.
Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...
Patients’ financial resources affect their enrollment in oncology clinical trials to a greater degree than traditional ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
HybridLeg robots Olaf and Snogie use impact-safe design and self-recovery to enable scalable, real-world hardware ...
de Filippis, R. and Al Foysal, A. (2026) Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data.
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