A novel MIL architecture predicts zero-inflated beta parameters for TPS distributions in NSCLC using slide-level supervision.
Un- certainty quantification for machine learning in healthcare: a survey
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A Temporal Fusion Transformer with CORAL ordinal layer and autoregressive Mixture Density Network generates multi-horizon probabilistic trajectories and decomposed uncertainty estimates for Alzheimer's progression on ADNI data.
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Distribution-based deep multiple instance learning for tumor proportion scoring in NSCLC
A novel MIL architecture predicts zero-inflated beta parameters for TPS distributions in NSCLC using slide-level supervision.
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Uncertainty-Aware Longitudinal Forecasting of Alzheimer's Disease Progression Using Deep Learning
A Temporal Fusion Transformer with CORAL ordinal layer and autoregressive Mixture Density Network generates multi-horizon probabilistic trajectories and decomposed uncertainty estimates for Alzheimer's progression on ADNI data.