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A Study of Deep Learning Colon Cancer Detection in Limited Data Access Scenarios., , , , and . CoRR, (2020)Measuring Domain Shift for Deep Learning in Histopathology., , , and . IEEE J. Biomed. Health Informatics, 25 (2): 325-336 (2021)Deep Learning for Digital Pathology in Limited Data Scenarios.. Linköping University, Sweden, (2022)base-search.net (ftlinkoepinguniv:oai:DiVA.org:liu-189009).Evaluation of Contrastive Predictive Coding for Histopathology Applications., , and . ML4H@NeurIPS, volume 136 of Proceedings of Machine Learning Research, page 328-340. PMLR, (2020)Correlated Feature Aggregation by Region Helps Distinguish Aggressive from Indolent Clear Cell Renal Cell Carcinoma Subtypes on CT., , , , , and . CoRR, (2022)Combatting out-of-distribution errors using model-agnostic meta-learning for digital pathology., , and . Medical Imaging: Digital Pathology, volume 11603 of SPIE Proceedings, SPIE, (2021)A Closer Look at Domain Shift for Deep Learning in Histopathology., , , and . CoRR, (2019)Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training., , , , , , , , , and 4 other author(s). J. Digit. Imaging, 34 (1): 105-115 (2021)Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications., , , and . CoRR, (2021)Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection., , , and . MICCAI (5), volume 12905 of Lecture Notes in Computer Science, page 624-633. Springer, (2021)