| Deep learning for healthcare: review, opportunities and challenges R Miotto, F Wang, S Wang, X Jiang, JT Dudley Briefings in bioinformatics 19 (6), 1236-1246, 2018 | 4008 | 2018 |
| Deep patient: an unsupervised representation to predict the future of patients from the electronic health records R Miotto, L Li, BA Kidd, JT Dudley Scientific reports 6 (1), 26094, 2016 | 2261 | 2016 |
| Artificial intelligence in cardiology KW Johnson, J Torres Soto, BS Glicksberg, K Shameer, R Miotto, M Ali, ... Journal of the American College of Cardiology 71 (23), 2668-2679, 2018 | 1406 | 2018 |
| AKI in hospitalized patients with COVID-19 L Chan, K Chaudhary, A Saha, K Chauhan, A Vaid, S Zhao, I Paranjpe, ... Journal of the American Society of Nephrology 32 (1), 151-160, 2021 | 1094* | 2021 |
| Natural language processing of clinical notes on chronic diseases: systematic review S Sheikhalishahi, R Miotto, JT Dudley, A Lavelli, F Rinaldi, V Osmani JMIR medical informatics 7 (2), e12239, 2019 | 631 | 2019 |
| Deep learning and the electrocardiogram: review of the current state-of-the-art S Somani, AJ Russak, F Richter, S Zhao, A Vaid, F Chaudhry, ... EP Europace 23 (8), 1179-1191, 2021 | 343 | 2021 |
| A functional genomics predictive network model identifies regulators of inflammatory bowel disease LA Peters, J Perrigoue, A Mortha, A Iuga, W Song, EM Neiman, ... Nature genetics 49 (10), 1437-1449, 2017 | 311 | 2017 |
| Coronavirus 2019 and people living with human immunodeficiency virus: outcomes for hospitalized patients in New York City K Sigel, T Swartz, E Golden, I Paranjpe, S Somani, F Richter, ... Clinical infectious diseases 71 (11), 2933-2938, 2020 | 304* | 2020 |
| Federated learning of electronic health records to improve mortality prediction in hospitalized patients with COVID-19: machine learning approach A Vaid, SK Jaladanki, J Xu, S Teng, A Kumar, S Lee, S Somani, ... JMIR medical informatics 9 (1), e24207, 2021 | 292 | 2021 |
| Machine learning to predict mortality and critical events in a cohort of patients with COVID-19 in New York City: model development and validation A Vaid, S Somani, AJ Russak, JK De Freitas, FF Chaudhry, I Paranjpe, ... Journal of medical Internet research 22 (11), e24018, 2020 | 267* | 2020 |
| Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams K Shameer, MA Badgeley, R Miotto, BS Glicksberg, JW Morgan, ... Briefings in bioinformatics 18 (1), 105-124, 2017 | 265 | 2017 |
| Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale I Landi, BS Glicksberg, HC Lee, S Cherng, G Landi, M Danieletto, ... npj Digital Medicine 3 (96), 2020 | 259 | 2020 |
| Predictive modeling of hospital readmission rates using electronic medical record-wide machine learning: a case-study using Mount Sinai heart failure cohort K Shameer, KW Johnson, A Yahi, R Miotto, LI Li, D Ricks, J Jebakaran, ... Pacific symposium on biocomputing 2017, 276-287, 2017 | 242 | 2017 |
| Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City I Paranjpe, AJ Russak, JK De Freitas, A Lala, R Miotto, A Vaid, ... BMJ open 10 (11), e040736, 2020 | 174* | 2020 |
| Use of physiological data from a wearable device to identify SARS-CoV-2 infection and symptoms and predict COVID-19 diagnosis: observational study RP Hirten, M Danieletto, L Tomalin, KH Choi, M Zweig, E Golden, S Kaur, ... Journal of medical Internet research 23 (2), e26107, 2021 | 166 | 2021 |
| Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials R Miotto, C Weng Journal of the American Medical Informatics Association 22 (e1), e141-e150, 2015 | 126 | 2015 |
| Automated disease cohort selection using word embeddings from Electronic Health Records BS Glicksberg, R Miotto, KW Johnson, K Shameer, L Li, R Chen, ... PACIFIC SYMPOSIUM on BIOCOMPUTING 2018: Proceedings of the Pacific Symposium …, 2018 | 107 | 2018 |
| Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning K Shameer, BS Glicksberg, R Hodos, KW Johnson, MA Badgeley, ... Briefings in bioinformatics 19 (4), 656-678, 2018 | 102 | 2018 |
| Deep learning to predict patient future diseases from the electronic health records R Miotto, L Li, JT Dudley European conference on information retrieval, 768-774, 2016 | 89 | 2016 |
| Reflecting health: smart mirrors for personalized medicine R Miotto, M Danieletto, JR Scelza, BA Kidd, JT Dudley NPJ digital medicine 1 (1), 62, 2018 | 68 | 2018 |
Joel DudleyInstitute Director and Associate Professor, Icahn School of Medicine at Mount SinaiVerified email at mssm.edu
