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Found 8 papers, 2 papers with code
Analysis | OPEN | Published: 17 June 2019 Multitask learning and benchmarking with clinical time series data
Health care is one of the most exciting frontiers in data mining and machine learning.
Effective Representations of Clinical Notes
We used the learned representations, along with commonly used bag of words and topic model representations, as features for predictive models of clinical events.
Multitask learning and benchmarking with clinical time series data
Health care is one of the most exciting frontiers in data mining and machine learning.
Intra-day Activity Better Predicts Chronic Conditions
In this work we investigate intra-day patterns of activity on a population of 7, 261 users of mobile health wearable devices and apps.
Toward Interpretable Topic Discovery via Anchored Correlation Explanation
Many predictive tasks, such as diagnosing a patient based on their medical chart, are ultimately defined by the decisions of human experts.
Modeling Missing Data in Clinical Time Series with RNNs
For linear models, we show an alternative strategy to capture this signal.
Learning to Diagnose with LSTM Recurrent Neural Networks
We present the first study to empirically evaluate the ability of LSTMs to recognize patterns in multivariate time series of clinical measurements.
Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks
We present a novel application of LSTM recurrent neural networks to multilabel classification of diagnoses given variable-length time series of clinical measurements.
