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cs.LG2022
Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Data
Joceline Ziegler, Bjarne Pfitzner, Heinrich Schulz +2
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper eval…
cs.LG2020
Localization of Critical Findings in Chest X-Ray without Local Annotations Using Multi-Instance Learning
Evan Schwab, André Gooßen, Hrishikesh Deshpande +1
The automatic detection of critical findings in chest X-rays (CXR), such as pneumothorax, is important for assisting radiologists in their clinical workflow like triaging time-sens…
cs.LG2020
Smart Chest X-ray Worklist Prioritization using Artificial Intelligence: A Clinical Workflow Simulation
Ivo M. Baltruschat, Leonhard Steinmeister, Hannes Nickisch +5
The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTAT) for criti…