| Phosphorus limitation of coastal ecosystem processes PV Sundareshwar, JT Morris, EK Koepfler, B Fornwalt Science 299 (5606), 563-565, 2003 | 476 | 2003 |
| Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration MR Arbabshirani, BK Fornwalt, GJ Mongelluzzo, JD Suever, BD Geise, ... NPJ digital medicine 1 (1), 1-7, 2018 | 397 | 2018 |
| Agreement is poor among current criteria used to define response to cardiac resynchronization therapy BK Fornwalt, WW Sprague, P BeDell, JD Suever, B Gerritse, JD Merlino, ... Circulation 121 (18), 1985-1991, 2010 | 362 | 2010 |
| 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 | 239 | 2020 |
| Routinely reported ejection fraction and mortality in clinical practice: where does the nadir of risk lie? GJ Wehner, L Jing, CM Haggerty, JD Suever, JB Leader, DN Hartzel, ... European Heart Journal 41 (12), 1249-1257, 2020 | 232 | 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 | 182 | 2021 |
| Predicting survival from large echocardiography and electronic health record datasets: optimization with machine learning MD Samad, A Ulloa, GJ Wehner, L Jing, D Hartzel, CW Good, BA Williams, ... JACC: Cardiovascular Imaging 12 (4), 681-689, 2019 | 172 | 2019 |
| Association Between Titin Loss-of-Function Variants and Early-Onset Atrial Fibrillation SH Choi, LC Weng, C Roselli, H Lin, CM Haggerty, MB Shoemaker, ... Jama 320 (22), 2354-2364, 2018 | 168 | 2018 |
| Genomics-first evaluation of heart disease associated with titin-truncating variants CM Haggerty, SM Damrauer, MG Levin, D Birtwell, DJ Carey, AM Golden, ... Circulation 140 (1), 42-54, 2019 | 133 | 2019 |
| A new method for the determination of aortic pulse wave velocity using cross‐correlation on 2D PCMR velocity data SW Fielden, BK Fornwalt, M Jerosch‐Herold, RL Eisner, AE Stillman, ... Journal of Magnetic Resonance Imaging 27 (6), 1382-1387, 2008 | 122 | 2008 |
| Cardiac remodeling and dysfunction in childhood obesity: a cardiovascular magnetic resonance study L Jing, CM Binkley, JD Suever, N Umasankar, CM Haggerty, J Rich, ... Journal of Cardiovascular Magnetic Resonance 18 (1), 1-12, 2016 | 84 | 2016 |
| Smooth muscle cell deletion of low-density lipoprotein receptor–related protein 1 augments angiotensin II–induced superior mesenteric arterial and ascending aortic aneurysms FM Davis, DL Rateri, A Balakrishnan, DA Howatt, DK Strickland, ... Arteriosclerosis, thrombosis, and vascular biology, ATVBAHA. 114.304683, 2014 | 69 | 2014 |
| A machine learning approach to management of heart failure populations L Jing, AE Ulloa Cerna, CW Good, NM Sauers, G Schneider, DN Hartzel, ... Heart Failure 8 (7), 578-587, 2020 | 66 | 2020 |
| Predicting deterioration of ventricular function in patients with repaired tetralogy of Fallot using machine learning MD Samad, GJ Wehner, MR Arbabshirani, L Jing, AJ Powell, T Geva, ... European Heart Journal-Cardiovascular Imaging 19 (7), 730-738, 2018 | 65 | 2018 |
| Electronic health record phenotype in subjects with genetic variants associated with arrhythmogenic right ventricular cardiomyopathy: a study of 30,716 subjects with exome … CM Haggerty, CA James, H Calkins, C Tichnell, JB Leader, DN Hartzel, ... Genetics in Medicine 19 (11), 1245-1252, 2017 | 53 | 2017 |
| rECHOmmend: An ECG-Based Machine Learning Approach for Identifying Patients at Increased Risk of Undiagnosed Structural Heart Disease Detectable by Echocardiography AE Ulloa-Cerna, L Jing, JM Pfeifer, S Raghunath, JA Ruhl, DB Rocha, ... Circulation 146 (1), 36, 2022 | 52 | 2022 |
| Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality AE Ulloa Cerna, L Jing, CW Good, DP vanMaanen, S Raghunath, ... Nature Biomedical Engineering 5 (6), 546-554, 2021 | 52 | 2021 |
| Left and right ventricular dyssynchrony and strains from cardiovascular magnetic resonance feature tracking do not predict deterioration of ventricular function in patients … L Jing, GJ Wehner, JD Suever, RJ Charnigo, S Alhadad, E Stearns, ... Journal of Cardiovascular Magnetic Resonance 18 (1), 1-10, 2016 | 52 | 2016 |
| Patients with repaired tetralogy of Fallot suffer from intra-and inter-ventricular cardiac dyssynchrony: a cardiac magnetic resonance study L Jing, CM Haggerty, JD Suever, S Alhadad, A Prakash, F Cecchin, ... European Heart Journal-Cardiovascular Imaging 15 (12), 1333-1343, 2014 | 52 | 2014 |
| DiscovEHR study and the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium. Association between titin loss-of-function variants and early-onset atrial fibrillation SH Choi, LC Weng, C Roselli, H Lin, CM Haggerty, MB Shoemaker, ... JAMA 320 (22), 2354-2364, 2018 | 50 | 2018 |
