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Surgical data science - from concepts toward clinical translation., , , , , , , , , and 41 other author(s). Medical Image Anal., (2022)Robust Medical Instrument Segmentation Challenge 2019., , , , , , , , , and 40 other author(s). CoRR, (2020)Labeling instructions matter in biomedical image analysis., , , , , , , , , and . CoRR, (2022)MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images., , , , , , , , , and 24 other author(s). IEEE Trans. Medical Imaging, 41 (10): 2728-2738 (2022)Labelling instructions matter in biomedical image analysis., , , , , , , , , and . Nat. Mac. Intell., 5 (3): 273-283 (March 2023)Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room., , , , , , , , , and 20 other author(s). CoRR, (2020)Exploiting the potential of unlabeled endoscopic video data with self-supervised learning., , , , , , , , , and 3 other author(s). CoRR, (2017)Crowdtruth validation: a new paradigm for validating algorithms that rely on image correspondences., , , , , , , , , and 6 other author(s). Int. J. Comput. Assist. Radiol. Surg., 10 (8): 1201-1212 (2015)How can we learn (more) from challenges? A statistical approach to driving future algorithm development., , , , , , , , , and 5 other author(s). CoRR, (2021)Beyond rankings: Learning (more) from algorithm validation., , , , , , , , , and 7 other author(s). Medical Image Anal., (May 2023)