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NPRL: Nightly Profile Representation Learning for Early Sepsis Onset Prediction in ICU Trauma Patients
Recently, deep learning methodologies have been proposed to predict sepsis, but some fail to capture the time of onset (e. g., classifying patients' entire visits as developing sepsis or not) and others are unrealistic for deployment in clinical settings (e. g., creating training instances using a fixed time to onset, where the time of onset needs to be known apriori).
Multi-Subset Approach to Early Sepsis Prediction
However, clinical scores like Sequential Organ Failure Assessment (SOFA) are not applicable for early prediction, while machine learning algorithms can help capture the progressing pattern for early prediction.
Enhancing Peak Network Traffic Prediction via Time-Series Decomposition
For network administration and maintenance, it is critical to anticipate when networks will receive peak volumes of traffic so that adequate resources can be allocated to service requests made to servers.
