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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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Other publications of authors with the same name

Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis., , , , , and . MIDL, volume 143 of Proceedings of Machine Learning Research, page 451-472. PMLR, (2021)Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening., , , , , , , , , and 22 other author(s). IEEE Trans. Medical Imaging, 39 (4): 1184-1194 (2020)Screening Mammogram Classification with Prior Exams., , , , , , , and . CoRR, (2019)Adaptive Early-Learning Correction for Segmentation from Noisy Annotations., , , , and . CVPR, page 2596-2606. IEEE, (2022)Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data., , , , , , and . CoRR, (2023)An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization., , , , , , , , , and 1 other author(s). Medical Image Anal., (2021)An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization., , , , , , , , , and 1 other author(s). CoRR, (2020)Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning., , , , , , and . CVPR, page 3355-3365. IEEE, (2023)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)Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening., , , , , , , , , and 22 other author(s). CoRR, (2019)