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Found 4 papers, 1 papers with code
HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data
The recent success of machine learning methods applied to time series collected from Intensive Care Units (ICU) exposes the lack of standardized machine learning benchmarks for developing and comparing such methods.
Ranked #1 on
Remaining Length of Stay
on HiRID
Early prediction of respiratory failure in the intensive care unit
The development of respiratory failure is common among patients in intensive care units (ICU).
Machine learning for early prediction of circulatory failure in the intensive care unit
Intensive care clinicians are presented with large quantities of patient information and measurements from a multitude of monitoring systems.
Improving Clinical Predictions through Unsupervised Time Series Representation Learning
In this work, we investigate unsupervised representation learning on medical time series, which bears the promise of leveraging copious amounts of existing unlabeled data in order to eventually assist clinical decision making.
