most citedWeakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features

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eess.IV2022

Co-occurring Diseases Heavily Influence the Performance of Weakly Supervised Learning Models for Classification of Chest CT

Fakrul Islam Tushar, Vincent M. D'Anniballe, Geoffrey D. Rubin +2

Despite the potential of weakly supervised learning to automatically annotate massive amounts of data, little is known about its limitations for use in computer-aided diagnosis (CA…

eess.IV2020

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…