Ben Glocker

TL;DR: In this paper , the authors performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER TBI) cohort.

TL;DR: An overview of potential attacks on collaborative machine learning and how these threats could be addressed is provided and a focused perspective on open challenges and promising areas of future research in the field is provided.

TL;DR: Jianningli et al. as mentioned in this paper provided a comprehensive overview of the MICCAI 2020 AutoImplant Challenge and the approaches and publications submitted and accepted within the challenge, highlighting common algorithmic trends and algorithmic diversity.

TL;DR: A fast, fully automated, and learning-based quality control pipeline for CMR images, specifically for short-axis image stacks, using a hybrid decision forest method to extract landmarks and probabilistic segmentation maps from both long- and short- axis images as a basis to perform the quality checks.

TL;DR: Gaussian Processes enables visualisation of nonlinear interactions between biomarkers, in individual patient biomarker ‘space', providing information for personalised or stratified healthcare or clinical trial design.