1 citations · 1 across the 4 of their papers we have counts for
5 papers
Improving Calibration of Black-Box Radiology AI Using Test-Time Augmentation
Nathan Le, Magdalini Paschali, Arogya Koirala +5
Radiology AI systems increasingly inform clinical decisions such as triage, follow-up imaging, and treatment planning. For these decisions to be made safely, model outputs must be…
Automated Real-time Assessment of Intracranial Hemorrhage Detection AI Using an Ensembled Monitoring Model (EMM)
Zhongnan Fang, Andrew Johnston, Lina Cheuy +10
Artificial intelligence (AI) tools for radiology are commonly unmonitored once deployed. The lack of real-time case-by-case assessments of AI prediction confidence requires users t…
Regulating radiology AI medical devices that evolve in their lifecycle
Camila González, Moritz Fuchs, Daniel Pinto dos Santos +9
Over time, the distribution of medical image data drifts due to factors such as shifts in patient demographics, acquisition devices, and disease manifestations. While human radiolo…
SOE: SO(3)-Equivariant 3D MRI Encoding
Shizhe He, Magdalini Paschali, Jiahong Ouyang +3
Representation learning has become increasingly important, especially as powerful models have shifted towards learning latent representations before fine-tuning for downstream task…
Spectral Graph Sample Weighting for Interpretable Sub-cohort Analysis in Predictive Models for Neuroimaging
Magdalini Paschali, Yu Hang Jiang, Spencer Siegel +4
Recent advancements in medicine have confirmed that brain disorders often comprise multiple subtypes of mechanisms, developmental trajectories, or severity levels. Such heterogenei…