96 citations · 129 across the 7 of their papers we have counts for
6 papers · 1 filter
Deep State-Space Generative Model For Correlated Time-to-Event Predictions
Yuan Xue, Denny Zhou, Nan Du +4
Capturing the inter-dependencies among multiple types of clinically-critical events is critical not only to accurate future event prediction, but also to better treatment planning.…
Brainformers: Trading Simplicity for Efficiency
Yanqi Zhou, Nan Du, Yanping Huang +12
Transformers are central to recent successes in natural language processing and computer vision. Transformers have a mostly uniform backbone where layers alternate between feed-for…
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems
Zhe Chen, Yuyan Wang, Dong Lin +4
Despite deep neural network (DNN)'s impressive prediction performance in various domains, it is well known now that a set of DNN models trained with the same model specification an…
Deep Physiological State Space Model for Clinical Forecasting
Yuan Xue, Denny Zhou, Nan Du +4
Clinical forecasting based on electronic medical records (EMR) can uncover the temporal correlations between patients' conditions and outcomes from sequences of longitudinal clinic…
Modelling EHR timeseries by restricting feature interaction
Kun Zhang, Yuan Xue, Gerardo Flores +3
Time series data are prevalent in electronic health records, mostly in the form of physiological parameters such as vital signs and lab tests. The patterns of these values may be s…
Explaining an increase in predicted risk for clinical alerts
Michaela Hardt, Alvin Rajkomar, Gerardo Flores +5
Much work aims to explain a model's prediction on a static input. We consider explanations in a temporal setting where a stateful dynamical model produces a sequence of risk estima…