Stacking Machine Learning Ensemble Predicts Ovarian Cancer Risk in Screening Cohort
A leakage-aware machine learning ensemble combining K-Nearest Neighbors and AdaBoost achieved an accuracy of 0.7644 in predicting ovarian cancer risk ...
A leakage-aware machine learning ensemble combining K-Nearest Neighbors and AdaBoost achieved an accuracy of 0.7644 in predicting ovarian cancer risk ...
A new AI framework combines retinal imaging with clinical vitals to assess cardiovascular disease risk, showing improved performance in women ...
A qualitative investigation in southern Brazil reveals that community sustainability training fosters an emerging ontological reorientation among rural women, transforming ...
Researchers have introduced a robust feature similarity learning framework that achieves high deepfake detection accuracy and withstands adversarial perturbations.
A systematic evaluation shows that feature selection performance in multiclass biomedical classification is highly dataset-dependent, with SHAP excelling on eco-medical ...
A new framework combining an Unscented Kalman Filter and a Graph Neural Network effectively assesses stability and power quality in ...
Researchers developed PMSL-YOLO, a lightweight progressive multi-scale training framework based on YOLOv8n that improves multi-disease detection in chest X-rays on ...
A new statistical framework analyzes the full temporal trajectory of RT-QuIC assays in prion disease, identifying distinct kinetic profiles that ...
Researchers from the PANDA Collaboration have demonstrated that geometric deep learning algorithms can effectively reconstruct particle tracks in the non-Euclidean ...
Published in Discover Quantum Science , the study analyzes data from Qatar Insurance Company (QIC) to show that leveraging quantum ...
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© 2026 Scienmag - Science Magazine