Silvie Opolka, Oleksandr Pometun, Krishnendu Bose, Srishti Pandey, Yulia Terekhova, Franziska Tietze, Sarmad Shoaib Baig, Lukas Niehaus · Current Directions in Biomedical Engineering 2026 · 2026
DOI: 10.1515/cdbme-2026-0193
Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).
We adapted two explainability methods commonly used in image classification, KernelSHAP and Grad-CAM, to colonoscopy video classification.We evaluated their plausibility by measuring how well their approximation of EndoFMLV’s visual focus for polyp class predictions aligned with the visible polyp region. Both methods showed low plausibility, and plausibility alone could not reveal model faults reliably.
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