215 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Heidelberg UniversityDE14 papers
- National Center for Tumor DiseasesDE14 papers
- University Hospital HeidelbergDE14 papers
- University Hospital Carl Gustav CarusDE11 papers
- Fresenius (Germany)DE9 papers
- RWTH Aachen UniversityDE9 papers
- Universitätsklinikum AachenDE5 papers
- German Cancer Research CenterDE4 papers
- Deutsches Herzzentrum MünchenDE3 papers
- Stanford UniversityUS3 papers
- Technical University of MunichDE3 papers
- Technische Universität DresdenDE3 papers
7 papers · 1 filter
Gut decisions based on the liver: A radiomics approach to boost colorectal cancer screening
Anna Hinterberger, Jonas Bohn, Dasha Trofimova +13
Non-invasive colorectal cancer (CRC) screening represents a key opportunity to improve colonoscopy participation rates and reduce CRC mortality. This study explores the potential o…
Hallucination Filtering in Radiology Vision-Language Models Using Discrete Semantic Entropy
Patrick Wienholt, Sophie Caselitz, Robert Siepmann +6
To determine whether using discrete semantic entropy (DSE) to reject questions likely to generate hallucinations can improve the accuracy of black-box vision-language models (VLMs)…
Resolution scaling governs DINOv3 transfer performance in chest radiograph classification
Soroosh Tayebi Arasteh, Mina Shaigan, Christiane Kuhl +3
Self-supervised learning (SSL) has improved visual representation learning, but its value in chest radiography remains uncertain. DINOv3 extends earlier SSL models through Gram-anc…
Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge
Max Kirchner, Hanna Hoffmann, Alexander C. Jenke +16
Developing generalizable surgical AI requires multi-institutional data, yet privacy constraints preclude direct data sharing, making Federated Learning (FL) a natural candidate. It…
MedicalPatchNet: A Patch-Based Self-Explainable AI Architecture for Chest X-ray Classification
Patrick Wienholt, Christiane Kuhl, Jakob Nikolas Kather +2
Deep neural networks excel in radiological image classification but frequently suffer from poor interpretability, limiting clinical acceptance. We present MedicalPatchNet, an inher…
Generating Reliable Synthetic Clinical Trial Data: The Role of Hyperparameter Optimization and Domain Constraints
Waldemar Hahn, Jan-Niklas Eckardt, Christoph Röllig +3
The generation of synthetic clinical trial data offers a promising approach to mitigating privacy concerns and data accessibility limitations in medical research. However, ensuring…
Enhanced Anomaly Detection for Capsule Endoscopy Using Ensemble Learning Strategies
Julia Werner, Christoph Gerum, Jorg Nick +4
Capsule endoscopy is a method to capture images of the gastrointestinal tract and screen for diseases which might remain hidden if investigated with standard endoscopes. Due to the…