Linda Moy
Linda Moy
New York University School of Medicine
Verified email at - Homepage
Cited by
Cited by
The sequence of the human genome
JC Venter, MD Adams, EW Myers, PW Li, RJ Mural, GG Sutton, HO Smith, ...
science 291 (5507), 1304-1351, 2001
Learning from crowds.
VC Raykar, S Yu, LH Zhao, GH Valadez, C Florin, L Bogoni, L Moy
Journal of machine learning research 11 (4), 2010
Checklist for artificial intelligence in medical imaging (CLAIM): a guide for authors and reviewers
J Mongan, L Moy, CE Kahn Jr
Radiology: Artificial Intelligence 2 (2), e200029, 2020
Breast cancer screening in women at higher-than-average risk: recommendations from the ACR
DL Monticciolo, MS Newell, L Moy, B Niell, B Monsees, EA Sickles
Journal of the American College of Radiology 15 (3), 408-414, 2018
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
Breast MRI: state of the art
RM Mann, N Cho, L Moy
Radiology 292 (3), 520-536, 2019
ChatGPT and other large language models are double-edged swords
Y Shen, L Heacock, J Elias, KD Hentel, B Reig, G Shih, L Moy
Radiology 307 (2), e230163, 2023
Prospective comparison of mammography, sonography, and MRI in patients undergoing neoadjuvant chemotherapy for palpable breast cancer
E Yeh, P Slanetz, DB Kopans, E Rafferty, D Georgian-Smith, L Moy, ...
American Journal of Roentgenology 184 (3), 868-877, 2005
A comparison of whole-genome shotgun-derived mouse chromosome 16 and the human genome
RJ Mural, MD Adams, EW Myers, HO Smith, GLG Miklos, R Wides, ...
Science 296 (5573), 1661-1671, 2002
Supervised learning from multiple experts: whom to trust when everyone lies a bit
VC Raykar, S Yu, LH Zhao, A Jerebko, C Florin, GH Valadez, L Bogoni, ...
Proceedings of the 26th Annual international conference on machine learning …, 2009
Contrast‐enhanced MRI for breast cancer screening
RM Mann, CK Kuhl, L Moy
Journal of Magnetic Resonance Imaging 50 (2), 377-390, 2019
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
Breast cancer screening for average-risk women: recommendations from the ACR commission on breast imaging
DL Monticciolo, MS Newell, RE Hendrick, MA Helvie, L Moy, B Monsees, ...
Journal of the American College of Radiology 14 (9), 1137-1143, 2017
Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers—From the Radiology Editorial …
DA Bluemke, L Moy, MA Bredella, BB Ertl-Wagner, KJ Fowler, VJ Goh, ...
Radiology 294 (3), 487-489, 2020
Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer
EE Sigmund, GY Cho, S Kim, M Finn, M Moccaldi, JH Jensen, ...
Magnetic resonance in medicine 65 (5), 1437-1447, 2011
Artificial intelligence for mammography and digital breast tomosynthesis: current concepts and future perspectives
KJ Geras, RM Mann, L Moy
Radiology 293 (2), 246-259, 2019
Modeling annotator expertise: Learning when everybody knows a bit of something
Y Yan, R Rosales, G Fung, M Schmidt, G Hermosillo, L Bogoni, L Moy, ...
Proceedings of the thirteenth international conference on artificial …, 2010
Precision medicine and radiogenomics in breast cancer: new approaches toward diagnosis and treatment
K Pinker, J Chin, AN Melsaether, EA Morris, L Moy
Radiology 287 (3), 732-747, 2018
Specificity of mammography and US in the evaluation of a palpable abnormality: retrospective review
L Moy, PJ Slanetz, R Moore, S Satija, ED Yeh, KA McCarthy, D Hall, ...
Radiology 225 (1), 176-181, 2002
Axillary nodal evaluation in breast cancer: state of the art
JM Chang, JWT Leung, L Moy, SM Ha, WK Moon
Radiology 295 (3), 500-515, 2020
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