3 citations · 5 across the 4 of their papers we have counts for
5 papers · 1 filter
Deep Semi-Supervised Embedded Clustering (DSEC) for Stratification of Heart Failure Patients
Oliver Carr, Stojan Jovanovic, Luca Albergante +6
Determining phenotypes of diseases can have considerable benefits for in-hospital patient care and to drug development. The structure of high dimensional data sets such as electron…
Prediction of the onset of cardiovascular diseases from electronic health records using multi-task gated recurrent units
Fernando Andreotti, Frank S. Heldt, Basel Abu-Jamous +8
In this work, we propose a multi-task recurrent neural network with attention mechanism for predicting cardiovascular events from electronic health records (EHRs) at different time…
Detection of REM Sleep Behaviour Disorder by Automated Polysomnography Analysis
Navin Cooray, Fernando Andreotti, Christine Lo +3
Evidence suggests Rapid-Eye-Movement (REM) Sleep Behaviour Disorder (RBD) is an early predictor of Parkinson's disease. This study proposes a fully-automated framework for RBD dete…
SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging
Huy Phan, Fernando Andreotti, Navin Cooray +2
Automatic sleep staging has been often treated as a simple classification problem that aims at determining the label of individual target polysomnography (PSG) epochs one at a time…
Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification
Huy Phan, Fernando Andreotti, Navin Cooray +2
Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This work proposes a joint classification-and-prediction framework based on CNNs for aut…