469 citations · 757 across the 20 of their papers we have counts for
4 papers · 1 filter
Current validation practice undermines surgical AI development
Annika Reinke, Ziying O. Li, Minu D. Tizabi +98
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…
Benchmarking and Evaluation of AI Models in Biology: Outcomes and Recommendations from the CZI Virtual Cells Workshop
Elizabeth Fahsbender, Alma Andersson, Jeremy Ash +32
Artificial intelligence holds immense promise for transforming biology, yet a lack of standardized, cross domain, benchmarks undermines our ability to build robust, trustworthy mod…
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…
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…