| 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 | 2568 | 2018 |
| Early-learning regularization prevents memorization of noisy labels S Liu, J Niles-Weed, N Razavian, C Fernandez-Granda arXiv preprint arXiv:2007.00151, 2020 | 623 | 2020 |
| 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 | 421 | 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 | 274 | 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 | 202 | 2016 |
| 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), 80, 2021 | 141 | 2021 |
| Deep ehr: Chronic disease prediction using medical notes J Liu, Z Zhang, N Razavian Machine Learning for Healthcare Conference, 440-464, 2018 | 139 | 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 | 117 | 2019 |
| 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), 2021 | 104 | 2021 |
| Generalizable deep learning model for early Alzheimer’s disease detection from structural MRIs S Liu, AV Masurkar, H Rusinek, J Chen, B Zhang, W Zhu, ... Scientific reports 12 (1), 17106, 2022 | 90 | 2022 |
| BERT-XML: Large scale automated ICD coding using BERT pretraining Z Zhang, J Liu, N Razavian arXiv preprint arXiv:2006.03685, 2020 | 86 | 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 | 81 | 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 | 73 | 2020 |
| Temporal convolutional neural networks for diagnosis from lab tests N Razavian, D Sontag arXiv preprint arXiv:1511.07938, 2015 | 73 | 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), 130, 2020 | 68 | 2020 |
| Detecting social and behavioral determinants of health with structured and free-text clinical data DJ Feller, OJB Don't Walk, J Zucker, MT Yin, P Gordon, N Elhadad Applied clinical informatics 11 (01), 172-181, 2020 | 63 | 2020 |
| Patient condition identification and treatment NS Razavian, S Blecker, AM Schmidt, A Smith-McLallen, S Nigam, ... US Patent App. 15/494,354, 2017 | 49 | 2017 |
| 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, 2019 | 46 | 2019 |
| Variationally regularized graph-based representation learning for electronic health records W Zhu, N Razavian Proceedings of the Conference on Health, Inference, and Learning, 1-13, 2021 | 43 | 2021 |
| Artificial intelligence and cancer O Troyanskaya, Z Trajanoski, A Carpenter, S Thrun, N Razavian, N Oliver Nature cancer 1 (2), 149-152, 2020 | 37 | 2020 |
