12 citations · 17 across the 3 of their papers we have counts for
3 papers
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data
Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle +35
Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Publ…
Representation Learning with Information Theory for COVID-19 Detection
Abel Díaz Berenguer, Tanmoy Mukherjee, Matias Bossa +2
Successful data representation is a fundamental factor in machine learning based medical imaging analysis. Deep Learning (DL) has taken an essential role in robust representation l…
On the Composition and Limitations of Publicly Available COVID-19 X-Ray Imaging Datasets
Beatriz Garcia Santa Cruz, Jan Sölter, Matias Nicolas Bossa +1
Machine learning based methods for diagnosis and progression prediction of COVID-19 from imaging data have gained significant attention in the last months, in particular by the use…