3 papers
cs.CV2026
Generalizing Abstention for Noise-Robust Learning in Medical Image Segmentation
Wesam Moustafa, Hossam Elsafty, Helen Schneider +2
Label noise is a critical problem in medical image segmentation, often arising from the inherent difficulty of manual annotation. Models trained on noisy data are prone to overfitt…
cs.AI2026
Benchmark Success, Clinical Failure: When Reinforcement Learning Optimizes for Benchmarks, Not Patients
Armin Berger, Manuela Bergau, Helen Schneider +7
Recent Reinforcement Learning (RL) advances for Large Language Models (LLMs) have improved reasoning tasks, yet their resource-constrained application to medical imaging remains un…
cs.LG2022
Improving Chest X-Ray Classification by RNN-based Patient Monitoring
David Biesner, Helen Schneider, Benjamin Wulff +2
Chest X-Ray imaging is one of the most common radiological tools for detection of various pathologies related to the chest area and lung function. In a clinical setting, automated…