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Yiqiu Shen
Tytuł
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Cytowane przez
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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, S Kim, L Moy, K Cho
arXiv preprint arXiv:1703.07047, 2017
1842017
Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms
T Schaffter, DSM Buist, CI Lee, Y Nikulin, D Ribli, Y Guan, W Lotter, Z Jie, ...
JAMA network open 3 (3), e200265-e200265, 2020
1592020
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
Prediction of total knee replacement and diagnosis of osteoarthritis by using deep learning on knee radiographs: data from the osteoarthritis initiative
K Leung, B Zhang, J Tan, Y Shen, KJ Geras, JS Babb, K Cho, G Chang, ...
Radiology 296 (3), 584, 2020
432020
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 12 (1), 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
Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms. JAMA Netw Open. 2020; 3 (3): 200265
T Schaffter, DSM Buist, CI Lee, Y Nikulin, D Ribli, Y Guan, W Lotter, Z Jie, ...
102020
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
Adaptive early-learning correction for segmentation from noisy annotations
S Liu, K Liu, W Zhu, Y Shen, C Fernandez-Granda
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
42022
Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms
N Wu, Z Huang, Y Shen, J Park, J Phang, T Makino, S Kim, K Cho, ...
arXiv preprint arXiv:2009.09282, 2020
32020
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
22021
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
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
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