1 code implementation • 8 Dec 2019 • John R. Zech, Jessica Zosa Forde, Michael L. Littman
Averaging predictions from 10 models reduced variability by nearly 70% (mean coefficient of variation from 0. 543 to 0. 169, t-test 15. 96, p-value < 0. 0001).
no code implementations • 8 Nov 2018 • Marcus A. Badgeley, John R. Zech, Luke Oakden-Rayner, Benjamin S. Glicksberg, Manway Liu, William Gale, Michael V. McConnell, Beth Percha, Thomas M. Snyder, Joel T. Dudley
In this study, we trained deep learning models on 17, 587 radiographs to classify fracture, five patient traits, and 14 hospital process variables.
no code implementations • 2 Jul 2018 • John R. Zech, Marcus A. Badgeley, Manway Liu, Anthony B. Costa, Joseph J. Titano, Eric K. Oermann
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 hospital or one group of hospitals will work equally well at different hospitals.
