1.7k citations · 1.7k across the 3 of their papers we have counts for
3 papers
The Utility of General Domain Transfer Learning for Medical Language Tasks
Daniel Ranti, Katie Hanss, Shan Zhao +4
The purpose of this study is to analyze the efficacy of transfer learning techniques and transformer-based models as applied to medical natural language processing (NLP) tasks, spe…
Confounding variables can degrade generalization performance of radiological deep learning models
John R. Zech, Marcus A. Badgeley, Manway Liu +3
Early results in using convolutional neural networks (CNNs) on x-rays to diagnose disease have been promising, but it has not yet been shown that models trained on x-rays from one…
Wide and deep volumetric residual networks for volumetric image classification
Varun Arvind, Anthony Costa, Marcus Badgeley +2
3D shape models that directly classify objects from 3D information have become more widely implementable. Current state of the art models rely on deep convolutional and inception m…