Daniel L. Rubin
Daniel L. Rubin
Stanford University
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Cited by
Cited by
Network analysis of intrinsic functional brain connectivity in Alzheimer's disease
K Supekar, V Menon, D Rubin, M Musen, MD Greicius
PLoS computational biology 4 (6), e1000100, 2008
BioPortal: ontologies and integrated data resources at the click of a mouse
NF Noy, NH Shah, PL Whetzel, B Dai, M Dorf, N Griffith, C Jonquet, ...
Nucleic acids research 37 (suppl_2), W170-W173, 2009
Deep learning for brain MRI segmentation: state of the art and future directions
Z Akkus, A Galimzianova, A Hoogi, DL Rubin, BJ Erickson
Journal of digital imaging 30, 449-459, 2017
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
KH Yu, C Zhang, GJ Berry, RB Altman, C Ré, DL Rubin, M Snyder
Nature communications 7 (1), 12474, 2016
Preparing medical imaging data for machine learning
MJ Willemink, WA Koszek, C Hardell, J Wu, D Fleischmann, H Harvey, ...
Radiology 295 (1), 4-15, 2020
A curated mammography data set for use in computer-aided detection and diagnosis research
RS Lee, F Gimenez, A Hoogi, KK Miyake, M Gorovoy, DL Rubin
Scientific data 4 (1), 1-9, 2017
PharmGKB: the pharmacogenetics knowledge base
M Hewett, DE Oliver, DL Rubin, KL Easton, JM Stuart, RB Altman, ...
Nucleic acids research 30 (1), 163-165, 2002
Content-based image retrieval in radiology: current status and future directions
CB Akgül, DL Rubin, S Napel, CF Beaulieu, H Greenspan, B Acar
Journal of digital imaging 24, 208-222, 2011
Integrating genotype and phenotype information: an overview of the PharmGKB project
TE Klein, JT Chang, MK Cho, KL Easton, R Fergerson, M Hewett, Z Lin, ...
The pharmacogenomics journal 1 (3), 167-170, 2001
MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set
DA Gutman, LAD Cooper, SN Hwang, CA Holder, JJ Gao, TD Aurora, ...
Radiology 267 (2), 560-569, 2013
Non–small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data—methods and preliminary results
O Gevaert, J Xu, CD Hoang, AN Leung, Y Xu, A Quon, DL Rubin, S Napel, ...
Radiology 264 (2), 387-396, 2012
Differential data augmentation techniques for medical imaging classification tasks
Z Hussain, F Gimenez, D Yi, D Rubin
AMIA annual symposium proceedings 2017, 979, 2017
Biomedical ontologies: a functional perspective
DL Rubin, NH Shah, NF Noy
Briefings in bioinformatics 9 (1), 75-90, 2008
The ACR BI-RADS® experience: learning from history
ES Burnside, EA Sickles, LW Bassett, DL Rubin, CH Lee, DM Ikeda, ...
Journal of the American College of Radiology 6 (12), 851-860, 2009
Deep learning in neuroradiology
G Zaharchuk, E Gong, M Wintermark, D Rubin, CP Langlotz
American Journal of Neuroradiology 39 (10), 1776-1784, 2018
Distributed deep learning networks among institutions for medical imaging
K Chang, N Balachandar, C Lam, D Yi, J Brown, A Beers, B Rosen, ...
Journal of the American Medical Informatics Association 25 (8), 945-954, 2018
Automated grading of gliomas using deep learning in digital pathology images: a modular approach with ensemble of convolutional neural networks
MG Ertosun, DL Rubin
AMIA annual symposium proceedings 2015, 1899, 2015
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
Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities
H Itakura, AS Achrol, LA Mitchell, JJ Loya, T Liu, EM Westbroek, ...
Science translational medicine 7 (303), 303ra138-303ra138, 2015
A randomized study of temozolomide or temozolomide and capecitabine in patients with advanced pancreatic neuroendocrine tumors: A trial of the ECOG-ACRIN Cancer Research Group …
PL Kunz, PJ Catalano, H Nimeiri, GA Fisher, TA Longacre, CJ Suarez, ...
Journal of Clinical Oncology 36 (15_suppl), 4004-4004, 2018
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