no code implementations • 12 Dec 2023 • John Metzcar, Catherine R. Jutzeler, Paul Macklin, Alvaro Köhn-Luque, Sarah C. Brüningk
This review aims to capture the current state of the field and provide a perspective on how mechanistic learning may further progress in mathematical oncology.
no code implementations • 6 Oct 2023 • Lucie Bourguignon, Caroline Weis, Catherine R. Jutzeler, Michael Adamer
Machine learning and deep learning have been celebrating many successes in the application to biological problems, especially in the domain of protein folding.
no code implementations • 15 Nov 2021 • Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck, Sarah C. Brüningk
Owing to its pristine soft-tissue contrast and high resolution, structural magnetic resonance imaging (MRI) is widely applied in neurology, making it a valuable data source for image-based machine learning (ML) and deep learning applications.
no code implementations • 12 Nov 2020 • Sarah C. Brüningk, Felix Hensel, Catherine R. Jutzeler, Bastian Rieck
Alzheimer's disease (AD) is associated with local (e. g. brain tissue atrophy) and global brain changes (loss of cerebral connectivity), which can be detected by high-resolution structural magnetic resonance imaging.