First Place in the STOIC Challenge: Prediction of COVID Severity with Convolutional Neural Networks

Daniel Kienzle, Julian Lorenz, Katja Ludwig, Robin Schön and Rainer Lienhart from the chair for Machine Learning and Computer Vision achieved the first place in the STOIC challenge. The goal of the challenge was to predict the severe outcome of COVID-19 one month ahead using CT scans. To this end, the researchers employed convolutional neural networks and transfer learning on various tasks. The challenge was organized by Assistance Publique – Hôpitaux de Paris, Radboud University Medical Center, and Amazon Web Services.