output
20202026
most citedDeep Learning in current Neuroimaging: a multivariate approach with power and type I error control but arguable generalization ability

24 citations

7 papers

cs.HC2026★ 1 cited

DR. INFO at the Point of Care: A Prospective Pilot Study of Physician-Perceived Value of an Agentic AI Clinical Assistant

Rogerio Corga Da Silva, Miguel Romano, Tiago Mendes +6

Background: Clinical documentation and information retrieval consume over half of physicians working hours, contributing to cognitive overload and burnout. While artificial intelli…

q-bio.QM2024★ 3 cited

Privacy-Preserving Multi-Center Differential Protein Abundance Analysis with FedProt

Yuliya Burankova, Miriam Abele, Mohammad Bakhtiari +28

Quantitative mass spectrometry has revolutionized proteomics by enabling simultaneous quantification of thousands of proteins. Pooling patient-derived data from multiple institutio…

stat.ME2024★ 4 cited

Statistical modeling to adjust for time trends in adaptive platform trials utilizing non-concurrent controls

Pavla Krotka, Martin Posch, Mohamed Gewily +2

Utilizing non-concurrent control data (NCC) in the analysis of late-entering arms in platform trials has recently received considerable attention. While incorporating NCC can lead…

cs.CV2022★ 20 cited

blob loss: instance imbalance aware loss functions for semantic segmentation

Florian Kofler, Suprosanna Shit, Ivan Ezhov +14

Deep convolutional neural networks (CNN) have proven to be remarkably effective in semantic segmentation tasks. Most popular loss functions were introduced targeting improved volum…

q-bio.TO2022★ 6 cited

Retina organoids: Window into the biophysics of neuronal systems

Katja A. Salbaum, Elijah R. Shelton, Friedhelm Serwane

With a kind of magnetism, the human retina draws the eye of neuroscientist and physicist alike. It is attractive as a self-organizing system, which forms as a part of the central n…

stat.ML2021★ 24 cited

Deep Learning in current Neuroimaging: a multivariate approach with power and type I error control but arguable generalization ability

Carmen Jiménez-Mesa, Javier Ramírez, John Suckling +5

Discriminative analysis in neuroimaging by means of deep/machine learning techniques is usually tested with validation techniques, whereas the associated statistical significance r…

eess.IV2020★ 5 cited

Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease

Martin Dyrba, Moritz Hanzig, Slawek Altenstein +37

Background: Although convolutional neural networks (CNN) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI)…