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Globally-Aware Multiple Instance Classifier for Breast Cancer Screening.

, , , , , , , and . MLMI@MICCAI, volume 11861 of Lecture Notes in Computer Science, page 18-26. Springer, (2019)

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Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks., , and . CoRR, (2018)An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization., , , , , , , , , and 1 other author(s). CoRR, (2020)Globally-Aware Multiple Instance Classifier for Breast Cancer Screening., , , , , , , and . MLMI@MICCAI, volume 11861 of Lecture Notes in Computer Science, page 18-26. Springer, (2019)Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability., , and . CoRR, (2020)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models, , , , , , , , , and 441 other author(s). (2022)cite arxiv:2206.04615Comment: 27 pages, 17 figures + references and appendices, repo: https://github.com/google/BIG-bench.Improving localization-based approaches for breast cancer screening exam classification., , , , , , and . CoRR, (2019)Unsupervised Sentence Compression using Denoising Auto-Encoders., and . CoNLL, page 413-422. Association for Computational Linguistics, (2018)Screening Mammogram Classification with Prior Exams., , , , , , , and . CoRR, (2019)Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening., , , , , , , , , and 22 other author(s). IEEE Trans. Medical Imaging, 39 (4): 1184-1194 (2020)Do Attention Heads in BERT Track Syntactic Dependencies?, , , and . CoRR, (2019)