| 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 | 606 | 2018 |
| 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 | 138 | 2015 |
| Multi-task prediction of disease onsets from longitudinal laboratory tests N Razavian, J Marcus, D Sontag Machine learning for healthcare conference, 73-100, 2016 | 114 | 2016 |
| Deep ehr: Chronic disease prediction using medical notes J Liu, Z Zhang, N Razavian Machine Learning for Healthcare Conference, 440-464, 2018 | 45 | 2018 |
| Temporal convolutional neural networks for diagnosis from lab tests N Razavian, D Sontag arXiv preprint arXiv:1511.07938, 2015 | 42 | 2015 |
| 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 | 35 | 2019 |
| 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), e0215571, 2019 | 21 | 2019 |
| Document representation and quality of text: An analysis M Keikha, NS Razavian, F Oroumchian, HS Razi Survey of text mining II, 219-232, 2008 | 20 | 2008 |
| Early detection of diabetes from health claims R Krishnan, N Razavian, Y Choi, S Nigam, S Blecker, A Schmidt, ... Machine Learning in Healthcare Workshop, NIPS, 1-5, 2013 | 14 | 2013 |
| 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 | 12 | 2019 |
| An overview of nonparametric bayesian models and applications to natural language processing N Sharif-Razavian, A Zollmann Science, 71-93, 2008 | 10 | 2008 |
| Learning generative models of molecular dynamics NS Razavian, H Kamisetty, CJ Langmead BMC genomics 13 (1), 1-13, 2012 | 9 | 2012 |
| The von mises graphical model: structure learning NS Razavian, H Kamisetty, CJ Langmead Technical Report CMU-CS-11-108, Carnegie Mellon University, 2011 | 9 | 2011 |
| Fixed length word suffix for factored statistical machine translation NS Razavian, S Vogel Proceedings of the ACL 2010 Conference Short Papers, 147-150, 2010 | 9 | 2010 |
| 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 | 8 | 2011 |
| Early-learning regularization prevents memorization of noisy labels S Liu, J Niles-Weed, N Razavian, C Fernandez-Granda arXiv preprint arXiv:2007.00151, 2020 | 7 | 2020 |
| Time-varying gaussian graphical models of molecular dynamics data NS Razavian, S Moitra, H Kamisetty, A Ramanathan, CJ Langmead Proceedings of 3DSIG, 2010 | 6 | 2010 |
| The web as a platform to build machine translation resources NS Razavian, S Vogel Proceedings of the 2009 international workshop on Intercultural …, 2009 | 5 | 2009 |
| 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, ... arXiv preprint arXiv:2008.01774, 2020 | 4 | 2020 |
| Augmented reality microscopes for cancer histopathology N Razavian Nature medicine 25 (9), 1334-1336, 2019 | 4 | 2019 |
