most citedThe STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

eess.IV2023★ 2 cited

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…

eess.IV2023

Towards Automated COVID-19 Presence and Severity Classification

Dominik Müller, Niklas Schröter, Silvan Mertes +6

COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times. Especially for capacity planning of…