Peer-Reviewed Publication
NPJ Digit Med2026;9(1)August 10, 2026Letter
Reply to: Surgical scene understanding and the emerging challenge of independent validation in an industry-led AI ecosystem.
Matthias Carstens1,2, Shubha Vasisht3, Zheyuan Zhang1, Iulia Barbur3, Annika Reinke4,5, Lena Maier-Hein4,5,6,7,8,9, Daniel A Hashimoto3,10, Fiona R Kolbinger11,12,13
1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.
2Department of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine, TUD Dresden University of Technology, Dresden, Germany.
3Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
4Division of Intelligent Medical Systems (IMSY), German Cancer Research Center (DKFZ), Heidelberg, Germany.
5Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany.
6Surgical AI Research Group, Heidelberg University Hospital, Heidelberg, Germany.
7National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany.
8Faculty of Mathematics and Computer Sciences, Heidelberg University, Heidelberg, Germany.
9Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab Emirates.
10Department of Computer and Information Science, University of Pennsylvania School of Engineering and Applied Science, Philadelphia, PA, USA.
11Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA. fiona.kolbinger@tu-dresden.de.
12Department of Visceral, Thoracic and Vascular Surgery, University Hospital and Faculty of Medicine, TUD Dresden University of Technology, Dresden, Germany. fiona.kolbinger@tu-dresden.de.
13Else Kröner Fresenius Center for Digital Health, Medical Faculty and University Hospital Dresden, TUD Dresden University of Technology, Dresden, Germany. fiona.kolbinger@tu-dresden.de.
Abstract
In this reply to MacAonghusa and Cahill, we reflect on fundamental validation challenges in AI-enabled surgical scene understanding and propose key priorities that academic, clinical, and industry stakeholders must collaboratively address to achieve safe and impactful clinical translation of surgical video AI: First, tying descriptive analytics to outcomes that matter to patients or surgical teams…
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