Image analysis for Alzheimer's disease prediction: Embracing pathological hallmarks for model architecture design. - Sarah C. Brüningk; Felix Hensel; Catherine R. Jutzeler; Bastian Rieck (CoRR, 2020)

Excitatory and inhibitory responses in the brain to experimental pain: A systematic review of MR spectroscopy studies. - Jessica Archibald; Erin L. MacMillan; Alinda Enzler; Catherine R. Jutzeler; Petra Schweinhardt; John L. K. Kramer (NeuroImage, 2020)

Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning. - Christian Bock; Michael Moor; Catherine R. Jutzeler; Karsten M. Borgwardt (Artificial Neural Networks, 3rd Edition, 2021)

Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer's Disease classification. - Sarah C. Brüningk; Felix Hensel; Louis P. Lukas; Merel Kuijs; Catherine R. Jutzeler; Bastian Rieck (MLHC, 2021)

Interpretability Aware Model Training to Improve Robustness against Out-of-Distribution Magnetic Resonance Images in Alzheimer's Disease Classification. - Merel Kuijs; Catherine R. Jutzeler; Bastian Rieck; Sarah C. Brüningk (CoRR, 2021)

Single-trial averaging improves the physiological interpretation of contact heat evoked potentials. - Catherine R. Jutzeler; Lukas D. Linde; Jan Rosner; Michèle Hubli; Armin Curt; John L. K. Kramer (NeuroImage, 2021)

Machine Learning in Medicine. - Catherine R. Jutzeler; Karsten M. Borgwardt (Mach. Learn. under Resour. Constraints Vol. 3 (3), 2022)

Genetic prediction of quantitative traits: a machine learner's guide focused on height. - Lucie Bourguignon; Caroline Weis; Catherine R. Jutzeler; Michael F. Adamer (CoRR, 2023)

Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain Patients. - Maria Monzon; Thomas Iff; Ender Konukoglu; Catherine R. Jutzeler (CoRR, 2024)