Hybrid GBT and attention-based MIL model achieves AUC 0.879 for PVH and 0.848 for NPVH on held-out test data, outperforming challenge baselines of 0.82 and 0.77.
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Neck-Learn: Attention-Based Multiple Instance Learning and Ensemble Framework for Ecological Momentary Assessment
Hybrid GBT and attention-based MIL model achieves AUC 0.879 for PVH and 0.848 for NPVH on held-out test data, outperforming challenge baselines of 0.82 and 0.77.