A hybrid framework uses adaptive bin partitioning, CVAE, multistage oversampling, LDWL loss, and gated fusion to improve performance on imbalanced regression benchmarks.
, author Pannu, H.S
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Stacking ensemble of RF, LightGBM, and DNN achieves NPV greater than 99.9% on internal test sets for meningitis detection in ICU despite class imbalance, with robust sensitivity on external eICU data.
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Hybrid Imbalanced Regression Through Unified Data-Level and Algorithm-Level Balancing
A hybrid framework uses adaptive bin partitioning, CVAE, multistage oversampling, LDWL loss, and gated fusion to improve performance on imbalanced regression benchmarks.
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Ensemble Deep Learning Models for Early Detection of Meningitis in ICU: Multi-center Study
Stacking ensemble of RF, LightGBM, and DNN achieves NPV greater than 99.9% on internal test sets for meningitis detection in ICU despite class imbalance, with robust sensitivity on external eICU data.