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Found 4 papers, 2 papers with code
Inference with non-differentiable surrogate loss in a general high-dimensional classification framework
In this work, we propose a kernel-smoothed decorrelated score to construct hypothesis testing and interval estimations for the linear decision rule estimated using a piece-wise linear surrogate loss, which has a discontinuous gradient and non-regular Hessian.
Near-optimal Individualized Treatment Recommendations
These numerical studies have shown the usefulness of the proposed A-ITR framework.
Constructing Stabilized Dynamic Treatment Regimes
We propose a new method termed stabilized O-learning for deriving stabilized dynamic treatment regimes, which are sequential decision rules for individual patients that not only adapt over the course of the disease progression but also remain consistent over time in format.
Methodology
Penalty-based spatial smoothing and outlier detection for childhood obesity surveillance from electronic health records
Childhood obesity is associated with increased morbidity and mortality in adulthood, leading to substantial healthcare cost.
Methodology Applications
