Narges Razavian
Narges Razavian
New York University Medical Center
Verified email at nyumc.org - Homepage
TitleCited byYear
Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
N Coudray, PS Ocampo, T Sakellaropoulos, N Narula, M Snuderl, ...
Nature medicine 24 (10), 1559-1567, 2018
2372018
Population-level prediction of type 2 diabetes from claims data and analysis of risk factors
N Razavian, S Blecker, AM Schmidt, A Smith-McLallen, S Nigam, ...
Big Data 3 (4), 277-287, 2015
932015
Multi-task prediction of disease onsets from longitudinal laboratory tests
N Razavian, J Marcus, D Sontag
Machine Learning for Healthcare Conference, 73-100, 2016
782016
Temporal convolutional neural networks for diagnosis from lab tests
N Razavian, D Sontag
arXiv preprint arXiv:1511.07938, 2015
282015
Deep ehr: Chronic disease prediction using medical notes
J Liu, Z Zhang, N Razavian
arXiv preprint arXiv:1808.04928, 2018
162018
Document representation and quality of text: An analysis
M Keikha, NS Razavian, F Oroumchian, HS Razi
Survey of Text Mining II, 219-232, 2008
162008
State of the art: Machine learning applications in glioma imaging
E Lotan, R Jain, N Razavian, GM Fatterpekar, YW Lui
American Journal of Roentgenology 212 (1), 26-37, 2019
132019
Early detection of diabetes from health claims
RG Krishnan, N Razavian, Y Choi, S Nigam, S Blecker, A Schmidt, ...
Machine Learning in Healthcare Workshop, NIPS, 2013
92013
Learning generative models of molecular dynamics
NS Razavian, H Kamisetty, CJ Langmead
BMC genomics 13 (S1), S5, 2012
92012
The von mises graphical model: structure learning
NS Razavian, H Kamisetty, CJ Langmead
Technical Report CMU-CS-11-108, Carnegie Mellon University, 2011
82011
Fixed length word suffix for factored statistical machine translation
NS Razavian, S Vogel
Proceedings of the ACL 2010 Conference Short Papers, 147-150, 2010
82010
The von mises graphical model: Regularized structure and parameter learning
N Razavian, H Kamisetty, CJ Langmead
Technical Report CMU-CS-11-129, Carnegie Mellon University, 2011
72011
An overview of nonparametric bayesian models and applications to natural language processing
N Sharif-Razavian, A Zollmann
Science, 71-93, 2008
72008
Time-varying gaussian graphical models of molecular dynamics data
NS Razavian, S Moitra, H Kamisetty, A Ramanathan, CJ Langmead
Proceedings of 3DSIG, 2010
62010
The web as a platform to build machine translation resources
NS Razavian, S Vogel
Proceedings of the 2009 international workshop on Intercultural …, 2009
52009
Predicting childhood obesity using electronic health records and publicly available data
R Hammond, R Athanasiadou, S Curado, Y Aphinyanaphongs, C Abrams, ...
PloS one 14 (4), 2019
42019
The von mises graphical model: Expectation propagation for inference
N Razavian, H Kamisetty, CJ Langmead
Technical Report CMU-CS-11-130, Carnegie Mellon University, 2011
42011
A deep learning approach for rapid mutational screening in melanoma
RH Kim, S Nomikou, Z Dawood, G Jour, D Donnelly, U Moran, JS Weber, ...
bioRxiv, 610311, 2019
32019
Determining EGFR and STK11 mutational status in lung adenocarcinoma histopathology images using deep learning
N Coudray, AL Moreira, T Sakellaropoulos, D Fenyö, N Razavian, ...
Cancer Research 78 (13 Supplement), 5309-5309, 2018
32018
Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors. Big Data. 2015; 3 (4): 277–87
N Razavian, S Blecker, AM Schmidt, A Smith-McLallen, S Nigam, ...
Epub 2016/07/22. https://doi. org/10.1089/big. 2015.0020 PMID: 27441408, 0
3
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