381 citations · 717 across the 31 of their papers we have counts for
9 papers · 1 filter
A Dataset and Benchmarks for Atrial Fibrillation Detection from Electrocardiograms of Intensive Care Unit Patients
Sarah Nassar, Nooshin Maghsoodi, Sophia Mannina +7
Objective: Atrial fibrillation (AF) is the most common cardiac arrhythmia experienced by intensive care unit (ICU) patients and can cause adverse health effects. In this study, we…
Domain Knowledge is Power: Leveraging Physiological Priors for Self Supervised Representation Learning in Electrocardiography
Nooshin Maghsoodi, Sarah Nassar, Paul F R Wilson +7
Objective: Electrocardiograms (ECGs) play a crucial role in diagnosing heart conditions; however, the effectiveness of artificial intelligence (AI)-based ECG analysis is often hind…
Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Minh Nguyen Nhat To, Paul F RWilson, Viet Nguyen +6
The subpopulationtion shift, characterized by a disparity in subpopulation distributibetween theween the training and target datasets, can significantly degrade the performance of…
PEP: Parameter Ensembling by Perturbation
Alireza Mehrtash, Purang Abolmaesumi, Polina Golland +3
Ensembling is now recognized as an effective approach for increasing the predictive performance and calibration of deep networks. We introduce a new approach, Parameter Ensembling…
Variational Learning with Disentanglement-PyTorch
Amir H. Abdi, Purang Abolmaesumi, Sidney Fels
Unsupervised learning of disentangled representations is an open problem in machine learning. The Disentanglement-PyTorch library is developed to facilitate research, implementatio…
A Preliminary Study of Disentanglement With Insights on the Inadequacy of Metrics
Amir H. Abdi, Purang Abolmaesumi, Sidney Fels
Disentangled encoding is an important step towards a better representation learning. However, despite the numerous efforts, there still is no clear winner that captures the indepen…
On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra-observer Variability in 2D Echocardiography Quality Assessment
Zhibin Liao, Hany Girgis, Amir Abdi +6
Uncertainty of labels in clinical data resulting from intra-observer variability can have direct impact on the reliability of assessments made by deep neural networks. In this pape…
Variational Shape Completion for Virtual Planning of Jaw Reconstructive Surgery
Amir H. Abdi, Mehran Pesteie, Eitan Prisman +2
The premorbid geometry of the mandible is of significant relevance in jaw reconstructive surgeries and occasionally unknown to the surgical team. In this paper, an optimization fra…
Deep Neural Maps
Mehran Pesteie, Purang Abolmaesumi, Robert Rohling
We introduce a new unsupervised representation learning and visualization using deep convolutional networks and self organizing maps called Deep Neural Maps (DNM). DNM jointly lear…