76 citations · 144 across the 12 of their papers we have counts for
13 papers
Contrastive Self-Supervised Learning for Spatio-Temporal Analysis of Lung Ultrasound Videos
Li Chen, Jonathan Rubin, Jiahong Ouyang +24
Self-supervised learning (SSL) methods have shown promise for medical imaging applications by learning meaningful visual representations, even when the amount of labeled data is li…
Parameter identification from single trajectory data: from linear to nonlinear
Xiaoyu Duan, Jonathan E Rubin, David Swigon
Our recent work lays out a general framework for inferring information about the parameters and associated dynamics of a differential equation model from a discrete set of data poi…
Convolution-Free Waveform Transformers for Multi-Lead ECG Classification
Annamalai Natarajan, Gregory Boverman, Yale Chang +2
We present our entry to the 2021 PhysioNet/CinC challenge - a waveform transformer model to detect cardiac abnormalities from ECG recordings. We compare the performance of the wave…
Interpretable Additive Recurrent Neural Networks For Multivariate Clinical Time Series
Asif Rahman, Yale Chang, Jonathan Rubin
Time series models with recurrent neural networks (RNNs) can have high accuracy but are unfortunately difficult to interpret as a result of feature-interactions, temporal-interacti…
CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation
Jonathan Rubin, S. Mazdak Abulnaga
Infarcted brain tissue resulting from acute stroke readily shows up as hyperintense regions within diffusion-weighted magnetic resonance imaging (DWI). It has also been proposed th…
Semi-supervised Learning for Quantification of Pulmonary Edema in Chest X-Ray Images
Ruizhi Liao, Jonathan Rubin, Grace Lam +5
We propose and demonstrate machine learning algorithms to assess the severity of pulmonary edema in chest x-ray images of congestive heart failure patients. Accurate assessment of…