102 citations · 140 across the 5 of their papers we have counts for
3 papers · 1 filter
Explainable multiple abnormality classification of chest CT volumes
Rachel Lea Draelos, Lawrence Carin
Understanding model predictions is critical in healthcare, to facilitate rapid verification of model correctness and to guard against use of models that exploit confounding variabl…
Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks
Rachel Lea Draelos, Lawrence Carin
Explanation methods facilitate the development of models that learn meaningful concepts and avoid exploiting spurious correlations. We illustrate a previously unrecognized limitati…
Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes
Rachel Lea Draelos, David Dov, Maciej A. Mazurowski +4
Machine learning models for radiology benefit from large-scale data sets with high quality labels for abnormalities. We curated and analyzed a chest computed tomography (CT) data s…