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06/28/2023
Increasing Performance And Sample Efficiency With Model-agnostic Interactive Feature Attributions
Model-agnostic feature attributions can provide local insights in comple...
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06/19/2023
Explaining the Model and Feature Dependencies by Decomposition of the Shapley Value
Shapley values have become one of the go-to methods to explain complex m...
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06/07/2023
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging
As machine learning becomes increasingly prevalent in critical fields su...
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03/27/2023
From the digital twins in healthcare to the Virtual Human Twin: a moon-shot project for digital health research
The idea of a systematic digital representation of the entire known huma...
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09/22/2022
EventNet: Detecting Events in EEG
Neurologists are often looking for various "events of interest" when ana...
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03/16/2021
Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones
The emergence of digital technologies such as smartphones in healthcare ...
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02/24/2021
Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach
Ischemic heart disease is the highest cause of mortality globally each y...
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08/21/2020
Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant Representation
Change point detection (CPD) aims to locate abrupt property changes in t...
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07/04/2020
Monitoring Depression in Bipolar Disorder using Circadian Measures from Smartphone Accelerometers
Current management of bipolar disorder relies on self-reported questionn...
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01/15/2020
Improving GANs for Speech Enhancement
Generative adversarial networks (GAN) have recently been shown to be eff...
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07/30/2019
Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning
Although large annotated sleep databases are publicly available, and mig...
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05/29/2019
NeoGuard: a public, online learning platform for neonatal seizures
Seizures occur in the neonatal period more frequently than other periods...
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04/11/2019
Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch
Many sleep studies suffer from the problem of insufficient data to fully...
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04/06/2019
Spatio-Temporal Attention Pooling for Audio Scene Classification
Acoustic scenes are rich and redundant in their content. In this work, w...
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11/12/2018
Detection of REM Sleep Behaviour Disorder by Automated Polysomnography Analysis
Evidence suggests Rapid-Eye-Movement (REM) Sleep Behaviour Disorder (RBD...
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11/02/2018
Beyond Equal-Length Snippets: How Long is Sufficient to Recognize an Audio Scene?
Due to the variability in characteristics of audio scenes, some can natu...
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11/02/2018
Unifying Isolated and Overlapping Audio Event Detection with Multi-Label Multi-Task Convolutional Recurrent Neural Networks
We propose a multi-label multi-task framework based on a convolutional r...
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09/28/2018
SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging
Automatic sleep staging has been often treated as a simple classificatio...
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09/19/2018
A unifying Bayesian approach for preterm brain-age prediction that models EEG sleep transitions over age
Preterm newborns undergo various stresses that may materialize as learni...
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05/16/2018
Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification
Sleep staging plays an important role in assessment and treatment of sle...
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06/29/2015