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Deep neural networks for automated classification of colorectal polyps on histopathology slides: A multi-institutional evaluation.

, , , , , , , , , , , , and . CoRR, (2019)

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Automated detection of celiac disease on duodenal biopsy slides: a deep learning approach., , , , , and . CoRR, (2019)Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images., , , , , , , and . CoRR, (2017)Masked Pre-Training of Transformers for Histology Image Analysis., , , and . CoRR, (2023)Deep neural networks for automated classification of colorectal polyps on histopathology slides: A multi-institutional evaluation., , , , , , , , , and 3 other author(s). CoRR, (2019)Application of machine learning on colonoscopy screening records for predicting colorectal polyp recurrence., , , and . BIBM, page 993-998. IEEE Computer Society, (2018)Natural Language Processing for Extracting Colorectal Polyp Information from Electronic Medical Records., , , , and . AMIA, AMIA, (2018)MHAttnSurv: Multi-Head Attention for Survival Prediction Using Whole-Slide Pathology Images., , and . CoRR, (2021)Difficulty Translation in Histopathology Images., , , , , , , and . AIME, volume 12299 of Lecture Notes in Computer Science, page 238-248. Springer, (2020)Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification., , , , , , , , , and 3 other author(s). WACV, page 2472-2482. IEEE, (2021)Generative Image Translation for Data Augmentation in Colorectal Histopathology Images., , , , , , and . ML4H@NeurIPS, volume 116 of Proceedings of Machine Learning Research, page 10-24. PMLR, (2019)