| 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 | 969 | 2018 |
| Prevalence and impact of myocardial injury in patients hospitalized with COVID-19 infection A Lala, KW Johnson, JL Januzzi, AJ Russak, I Paranjpe, F Richter, S Zhao, ... Journal of the American college of cardiology 76 (5), 533-546, 2020 | 830 | 2020 |
| Machine learning in cardiovascular medicine: are we there yet? K Shameer, KW Johnson, BS Glicksberg, JT Dudley, PP Sengupta Heart 104 (14), 1156-1164, 2018 | 470 | 2018 |
| Deep learning for cardiovascular medicine: a practical primer C Krittanawong, KW Johnson, RS Rosenson, Z Wang, M Aydar, U Baber, ... European heart journal 40 (25), 2058-2073, 2019 | 301 | 2019 |
| Machine learning prediction in cardiovascular diseases: a meta-analysis C Krittanawong, HUH Virk, S Bangalore, Z Wang, KW Johnson, R Pinotti, ... Scientific reports 10 (1), 16057, 2020 | 299 | 2020 |
| Pathology of peripheral artery disease in patients with critical limb ischemia N Narula, AJ Dannenberg, JW Olin, DL Bhatt, KW Johnson, G Nadkarni, ... Journal of the American College of Cardiology 72 (18), 2152-2163, 2018 | 246 | 2018 |
| Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network S Raghunath, AE Ulloa Cerna, L Jing, DP VanMaanen, J Stough, ... Nature medicine 26 (6), 886-891, 2020 | 230 | 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 | 200 | 2017 |
| 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 | 187 | 2020 |
| Deep neural networks can predict new-onset atrial fibrillation from the 12-lead ECG and help identify those at risk of atrial fibrillation–related stroke S Raghunath, JM Pfeifer, AE Ulloa-Cerna, A Nemani, T Carbonati, L Jing, ... Circulation 143 (13), 1287-1298, 2021 | 162 | 2021 |
| Proposed requirements for cardiovascular imaging-related machine learning evaluation (PRIME): a checklist: reviewed by the American College of Cardiology Healthcare Innovation … PP Sengupta, S Shrestha, B Berthon, E Messas, E Donal, GH Tison, ... Cardiovascular Imaging 13 (9), 2017-2035, 2020 | 156 | 2020 |
| Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management C Krittanawong, AJ Rogers, KW Johnson, Z Wang, MP Turakhia, ... Nature Reviews Cardiology 18 (2), 75-91, 2021 | 145 | 2021 |
| 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 | 145 | 2021 |
| Clinical characteristics of hospitalized Covid-19 patients in New York City I Paranjpe, AJ Russak, JK De Freitas, A Lala, R Miotto, A Vaid, ... MedRxiv, 2020.04. 19.20062117, 2020 | 126 | 2020 |
| Integrating blockchain technology with artificial intelligence for cardiovascular medicine C Krittanawong, AJ Rogers, M Aydar, E Choi, KW Johnson, Z Wang, ... Nature Reviews Cardiology 17 (1), 1-3, 2020 | 94 | 2020 |
| 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 | 86 | 2018 |
| 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 | 86 | 2018 |
| Enabling precision cardiology through multiscale biology and systems medicine KW Johnson, K Shameer, BS Glicksberg, B Readhead, PP Sengupta, ... Basic to Translational Science 2 (3), 311-327, 2017 | 82 | 2017 |
| Utilization of deep learning for subphenotype identification in sepsis-associated acute kidney injury K Chaudhary, A Vaid, Á Duffy, I Paranjpe, S Jaladanki, M Paranjpe, ... Clinical Journal of the American Society of Nephrology 15 (11), 1557-1565, 2020 | 79 | 2020 |
| Association of hemoglobin A1c levels with use of sulfonylureas, dipeptidyl peptidase 4 inhibitors, and thiazolidinediones in patients with type 2 diabetes treated with … R Vashisht, K Jung, A Schuler, JM Banda, RW Park, S Jin, L Li, JT Dudley, ... JAMA network open 1 (4), e181755-e181755, 2018 | 78 | 2018 |
