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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. Jastrzebski, T. Févry, J. Katsnelson, E. Kim, S. Wolfson, U. Parikh, S. Gaddam, L. Lin, K. Ho, J. Weinstein, B. Reig, Y. Gao, H. Toth, K. Pysarenko, A. Lewin, J. Lee, K. Airola, E. Mema, S. Chung, E. Hwang, N. Samreen, S. Kim, L. Heacock, L. Moy, K. Cho, and K. Geras. CoRR, (2019)

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Gene Boychuk

Gene Simat

Gene Zavadzkas

Gene Pang

Gene O Stimpson

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Application of independent component analysis with mixture density model to localize brain alpha activity in fMRI and EEG.J. Jeong, T. Kim, S. Kim, and M. Singh. Int. J. Imaging Syst. Technol., 14 (4): 170-180 (2004)Screening Mammogram Classification with Prior Exams.J. Park, J. Phang, Y. Shen, N. Wu, S. Kim, L. Moy, K. Cho, and K. Geras. CoRR, (2019)Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.N. Wu, J. Phang, J. Park, Y. Shen, Z. Huang, M. Zorin, S. Jastrzebski, T. Févry, J. Katsnelson, E. Kim and 22 other author(s). IEEE Trans. Medical Imaging, 39 (4): 1184-1194 (2020)Differentiation between glioblastomas and solitary brain metastases using diffusion tensor imaging.S. Wang, S. Kim, S. Chawla, R. Wolf, W. Zhang, D. O'Rourke, K. Judy, E. Melhem, and H. Poptani. NeuroImage, 44 (3): 653-660 (2009)Improving measurement of blood-brain barrier permeability with reduced scan time using deep-learning-derived capillary input function.J. Bae, C. Li, A. Masurkar, Y. Ge, and S. Kim. NeuroImage, (September 2023)Improving localization-based approaches for breast cancer screening exam classification.T. Févry, J. Phang, N. Wu, S. Kim, L. Moy, K. Cho, and K. Geras. CoRR, (2019)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, L. Heacock, L. Moy and 1 other author(s). CoRR, (2020)Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.N. Wu, J. Phang, J. Park, Y. Shen, Z. Huang, M. Zorin, S. Jastrzebski, T. Févry, J. Katsnelson, E. Kim and 22 other author(s). CoRR, (2019)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. Kim, K. Cho, L. Heacock, L. Moy and 1 other author(s). J. Digit. Imaging, 34 (6): 1414-1423 (2021)In vivo quantification of demyelination and recovery using compartment-specific diffusion MRI metrics validated by electron microscopy.I. Jelescu, M. Zurek, K. Winters, J. Veraart, A. Rajaratnam, N. Kim, J. Babb, T. Shepherd, D. Novikov, S. Kim and 1 other author(s). NeuroImage, (2016)

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Disambiguation of "Kim, Sungheon Gene"

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Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.

Please choose a person to relate this publication to

Gene Boychuk

Gene Simat

Gene Zavadzkas

Gene Pang

Gene O Stimpson

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Kim, Sungheon Gene"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.

Please choose a person to relate this publication to

Gene Boychuk

Gene Simat

Gene Zavadzkas

Gene Pang

Gene O Stimpson

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
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APA
Chicago
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Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.