output
20172026
most citedOn Leakage in Machine Learning Pipelines

68 citations

Showing 2024Show all

5 papers · 1 filter

eess.IV2024★ 8 cited

Unlocking the Potential of Digital Pathology: Novel Baselines for Compression

Maximilian Fischer, Peter Neher, Peter Schüffler +13

Digital pathology offers a groundbreaking opportunity to transform clinical practice in histopathological image analysis, yet faces a significant hurdle: the substantial file sizes…

physics.med-ph2024★ 6 cited

ezyMRI: How to build an MRI machine from scratch -- Experience from a four-day hackathon

Shaoying Huang, José Miguel Algarín, Joseba Alonso +25

Nuclear magnetic resonance instruments are becoming available to the do-it-yourself community. The challenges encountered in the endeavor to build a magnetic resonance imaging inst…

eess.IV2024★ 9 cited

Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge

Dominic LaBella, Ujjwal Baid, Omaditya Khanna +119

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in…

cs.CV2024★ 6 cited

Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model

Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson +5

Due to the sensitive nature of medicine, it is particularly important and highly demanded that AI methods are explainable. This need has been recognised and there is great research…

q-bio.TO2024★ 1 cited

An in-silico approach to meniscus tissue regeneration: Modeling, numerical simulation, and experimental analysis

Elise Grosjean, Alex Keilmann, Henry Jäger +10

We develop a model the dynamics of human mesenchymal stem cells (hMSCs) and chondrocytes evolving in a nonwoven polyethylene terephtalate (PET) scaffold impregnated with hyaluron a…