| 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 | 1322 | 2018 |
| Association of psychiatric disorders with mortality among patients with COVID-19 K Nemani, C Li, M Olfson, EM Blessing, N Razavian, J Chen, E Petkova, ... JAMA psychiatry 78 (4), 380-386, 2021 | 202 | 2021 |
| 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 | 187 | 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 | 153 | 2016 |
| Early-learning regularization prevents memorization of noisy labels S Liu, J Niles-Weed, N Razavian, C Fernandez-Granda arXiv preprint arXiv:2007.00151, 2020 | 129 | 2020 |
| Deep ehr: Chronic disease prediction using medical notes J Liu, Z Zhang, N Razavian Machine Learning for Healthcare Conference, 440-464, 2018 | 86 | 2018 |
| 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 | 63 | 2019 |
| 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, ... NPJ digital medicine 4 (1), 1-11, 2021 | 53 | 2021 |
| Temporal convolutional neural networks for diagnosis from lab tests N Razavian, D Sontag arXiv preprint arXiv:1511.07938, 2015 | 52 | 2015 |
| A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients N Razavian, VJ Major, M Sudarshan, J Burk-Rafel, P Stella, H Randhawa, ... NPJ digital medicine 3 (1), 1-13, 2020 | 40 | 2020 |
| 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 | 32 | 2019 |
| On the design of convolutional neural networks for automatic detection of Alzheimer’s disease S Liu, C Yadav, C Fernandez-Granda, N Razavian Machine Learning for Health Workshop, 184-201, 2020 | 23 | 2020 |
| BERT-XML: Large scale automated ICD coding using BERT pretraining Z Zhang, J Liu, N Razavian arXiv preprint arXiv:2006.03685, 2020 | 22 | 2020 |
| A deep learning approach for rapid mutational screening in melanoma RH Kim, S Nomikou, N Coudray, G Jour, Z Dawood, R Hong, E Esteva, ... BioRxiv, 610311, 2020 | 22 | 2020 |
| Document representation and quality of text: An analysis M Keikha, NS Razavian, F Oroumchian, HS Razi Survey of text mining II, 219-232, 2008 | 21 | 2008 |
| Patient condition identification and treatment NS Razavian, S Blecker, AM Schmidt, A Smith-McLallen, S Nigam, ... US Patent App. 15/494,354, 2017 | 20 | 2017 |
| Predicting endometrial cancer subtypes and molecular features from histopathology images using multi-resolution deep learning models R Hong, W Liu, D DeLair, N Razavian, D Fenyö Cell Reports Medicine 2 (9), 100400, 2021 | 18 | 2021 |
| 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 | 16 | 2013 |
| Artificial intelligence and cancer O Troyanskaya, Z Trajanoski, A Carpenter, S Thrun, N Razavian, N Oliver Nature Cancer 1 (2), 149-152, 2020 | 13 | 2020 |
| An overview of nonparametric bayesian models and applications to natural language processing N Sharif-Razavian, A Zollmann Science, 71-93, 2008 | 11 | 2008 |
