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Found 6 papers, 0 papers with code
BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis
Vision-and-language(V&L) models take image and text as input and learn to capture the associations between them.
Nonlinear Schrödinger Kernel for hardware acceleration in machine learning inference
Alternative machine learning approaches that are computationally light with low latency and can work with only a small training dataset are needed for applications where the insatiable demand of deep learning methods for computing power and large training data cannot be met.
Optics Signal Processing
Intra-Domain Task-Adaptive Transfer Learning to Determine Acute Ischemic Stroke Onset Time
We apply this approach to both 2D and 3D CNN architectures with our top model achieving an ROC-AUC value of 0. 74, with a sensitivity of 0. 70 and a specificity of 0. 81 for classifying TSS < 4. 5 hours.
Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography
The patient's OCT scan is predicted from three or two prior measurements.
Prostate cancer inference via weakly-supervised learning using a large collection of negative MRI
Here, we propose the baseline MRI model to alternatively learn the appearance of mp-MRI using radiology-confirmed negative MRI cases via weakly supervised learning.
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning
In this work, we present a novel convolutional neural net- work based method for perfusion map generation in dynamic suscepti- bility contrast-enhanced perfusion imaging.
