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Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU.

, , , , , , , , and . MLHC, volume 85 of Proceedings of Machine Learning Research, page 534-550. PMLR, (2018)

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Learning from Time Series under Temporal Label Noise., , , , , and . CoRR, (2024)Learning Unsupervised Representations for ICU Timeseries., , , , , , and . CHIL, volume 174 of Proceedings of Machine Learning Research, page 152-168. PMLR, (2022)Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU., , , , , , , , and . MLHC, volume 85 of Proceedings of Machine Learning Research, page 534-550. PMLR, (2018)Dynamic Interpretable Change Point Detection for Physiological Data Analysis., , , , and . ML4H@NeurIPS, volume 225 of Proceedings of Machine Learning Research, page 636-649. PMLR, (2023)Time-Varying Correlation Networks for Interpretable Change Point Detection., , and . CoRR, (2022)Decoupling Local and Global Representations of Time Series., , , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 8700-8714. PMLR, (2022)What went wrong and when? Instance-wise Feature Importance for Time-series Models., , , and . CoRR, (2020)Closed-Loop Neurostimulators: A Survey and A Seizure-Predicting Design Example for Intractable Epilepsy Treatment., , , , , , and . IEEE Trans. Biomed. Circuits Syst., 11 (5): 1026-1040 (2017)What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use., , , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 359-380. PMLR, (2019)Modeling personalized heart rate response to exercise and environmental factors with wearables data., , , , , and . npj Digit. Medicine, (2023)