8 papers
6 Fingers, 1 Kidney: Natural Adversarial Medical Images Reveal Critical Weaknesses of Vision-Language Models
Leon Mayer, Piotr Kalinowski, Caroline Ebersbach +6
Vision-language models (VLMs) are increasingly integrated into clinical workflows. However, existing benchmarks primarily assess performance on common anatomical presentations and…
Current validation practice undermines surgical AI development
Annika Reinke, Ziying O. Li, Minu D. Tizabi +97
Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains limited, with inadequate validation as an important contr…
Performance uncertainty in medical image analysis: a large-scale investigation of confidence intervals
Pascaline André, Charles Heitz, Evangelia Christodoulou +10
Performance uncertainty quantification is essential for reliable validation and eventual clinical translation of medical imaging artificial intelligence (AI). Confidence intervals…
Medical Imaging AI Competitions Lack Fairness
Annika Reinke, Evangelia Christodoulou, Sthuthi Sadananda +34
Benchmarking competitions are central to the development of artificial intelligence (AI) in medical imaging, defining performance standards and shaping methodological progress. How…
False Promises in Medical Imaging AI? Assessing Validity of Outperformance Claims
Evangelia Christodoulou, Annika Reinke, Pascaline Andrè +23
Performance comparisons are fundamental in medical imaging Artificial Intelligence (AI) research, often driving claims of superiority based on relative improvements in common perfo…
Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study
Leon Mayer, Tim Rädsch, Dominik Michael +8
While traditional computer vision models have historically struggled to generalize to endoscopic domains, the emergence of foundation models has shown promising cross-domain perfor…