Obserwuj
Nan Wu
Nan Wu
New York University, Center for Data Science
Zweryfikowany adres z nyu.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Deep neural networks improve radiologists’ performance in breast cancer screening
N Wu, J Phang, J Park, Y Shen, Z Huang, M Zorin, S Jastrzębski, T Févry, ...
IEEE transactions on medical imaging 39 (4), 1184-1194, 2019
2932019
High-resolution breast cancer screening with multi-view deep convolutional neural networks
KJ Geras, S Wolfson, Y Shen, N Wu, S Kim, E Kim, L Heacock, U Parikh, ...
arXiv preprint arXiv:1703.07047, 2017
1842017
Breast density classification with deep convolutional neural networks
N Wu, KJ Geras, Y Shen, J Su, SG Kim, E Kim, S Wolfson, L Moy, K Cho
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
642018
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
Y Shen, N Wu, J Phang, J Park, K Liu, S Tyagi, L Heacock, SG Kim, L Moy, ...
Medical image analysis 68, 101908, 2021
632021
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department
FE Shamout, Y Shen, N Wu, A Kaku, J Park, T Makino, S Jastrzębski, ...
NPJ digital medicine 4 (1), 1-11, 2021
562021
Globally-aware multiple instance classifier for breast cancer screening
Y Shen, N Wu, J Phang, J Park, G Kim, L Moy, K Cho, KJ Geras
International workshop on machine learning in medical imaging, 18-26, 2019
202019
Artificial Intelligence System Reduces False-Positive Findings in the Interpretation of Breast Ultrasound Exams
Y Shen, FE Shamout, JR Oliver, J Witowski, K Kannan, J Park, N Wu, ...
Nature Communications, 2021
192021
The NYU breast cancer screening dataset V1. 0
N Wu, J Phang, J Park, Y Shen, SG Kim, L Heacock, L Moy, K Cho, ...
New York Univ., New York, NY, USA, Tech. Rep, 2019
152019
SLAM: A unified encoder for speech and language modeling via speech-text joint pre-training
A Bapna, Y Chung, N Wu, A Gulati, Y Jia, JH Clark, M Johnson, J Riesa, ...
arXiv preprint arXiv:2110.10329, 2021
112021
Weakly-supervised high-resolution segmentation of mammography images for breast cancer diagnosis
K Liu, Y Shen, N Wu, J Chłędowski, C Fernandez-Granda, KJ Geras
Proceedings of machine learning research 143, 268, 2021
62021
Improving the ability of deep neural networks to use information from multiple views in breast cancer screening
N Wu, S Jastrzębski, J Park, L Moy, K Cho, KJ Geras
Medical Imaging with Deep Learning, 827-842, 2020
62020
Improving localization-based approaches for breast cancer screening exam classification
T Févry, J Phang, N Wu, S Kim, L Moy, K Cho, KJ Geras
arXiv preprint arXiv:1908.00615, 2019
62019
Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms
N Wu, Z Huang, Y Shen, J Park, J Phang, T Makino, S Gene Kim, K Cho, ...
Journal of Digital Imaging 34 (6), 1414-1423, 2021
5*2021
High-resolution breast cancer screening with multi-view deep convolutional neural networks. arXiv. 2017
KJ Geras, S Wolfson, Y Shen, N Wu, S Gene Kim, E Kim
arXiv preprint arXiv:1703.07047, 2019
52019
Screening Mammogram Classification with Prior Exams
J Park, J Phang, Y Shen, N Wu, S Kim, L Moy, K Cho, KJ Geras
arXiv preprint arXiv:1907.13057, 2019
12019
Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks
N Wu, S Jastrzębski, K Cho, KJ Geras
ICML 2022; arXiv preprint arXiv:2202.05306, 2022
2022
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency
FE Shamout, Y Shen, N Wu, A Kaku, J Park, T Makino, S Jastrzebski, ...
arXiv preprint arXiv:2008.01774, 2020
2020
Large-scale classification of breast MRI exams using deep convolutional networks
S Gong, M Muckley, N Wu, T Makino, SG Kim, L Heacock, L Moy, F Knoll, ...
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