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Found 4 papers, 2 papers with code
Explaining a machine learning decision to physicians via counterfactuals
Machine learning models perform well on several healthcare tasks and can help reduce the burden on the healthcare system.
PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation
The promise of Mobile Health (mHealth) is the ability to use wearable sensors to monitor participant physiology at high frequencies during daily life to enable temporally-precise health interventions.
Kernel Deformed Exponential Families for Sparse Continuous Attention
Theoretically, we show new existence results for both kernel exponential and deformed exponential families, and that the deformed case has similar approximation capabilities to kernel exponential families.
Transformers for prompt-level EMA non-response prediction
The transformer model achieves a non-response prediction AUC of 0. 77 and is significantly better than classical ML and LSTM-based deep learning models.
