| Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis F Maldonado, T Moua, S Rajagopalan, RA Karwoski, S Raghunath, ... European Respiratory Journal 43 (1), 204-212, 2014 | 227 | 2014 |
| 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 | 212 | 2020 |
| Automated quantitative computed tomography versus visual computed tomography scoring in idiopathic pulmonary fibrosis: validation against pulmonary function J Jacob, BJ Bartholmai, S Rajagopalan, M Kokosi, A Nair, R Karwoski, ... Journal of thoracic imaging 31 (5), 304-311, 2016 | 176 | 2016 |
| Quantitative computed tomography imaging of interstitial lung diseases BJ Bartholmai, S Raghunath, RA Karwoski, T Moua, S Rajagopalan, ... Journal of thoracic imaging 28 (5), 298-307, 2013 | 165 | 2013 |
| 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 | 148 | 2021 |
| Noninvasive characterization of the histopathologic features of pulmonary nodules of the lung adenocarcinoma spectrum using computer-aided nodule assessment and risk yield … F Maldonado, JM Boland, S Raghunath, MC Aubry, BJ Bartholmai, ... Journal of Thoracic Oncology 8 (4), 452-460, 2013 | 76 | 2013 |
| Pulmonary nodule characterization, including computer analysis and quantitative features BJ Bartholmai, CW Koo, GB Johnson, DB White, SM Raghunath, ... Journal of thoracic imaging 30 (2), 139-156, 2015 | 60 | 2015 |
| 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 | 57 | 2020 |
| Noninvasive computed tomography–based risk stratification of lung adenocarcinomas in the National Lung Screening Trial F Maldonado, F Duan, SM Raghunath, S Rajagopalan, RA Karwoski, ... American journal of respiratory and critical care medicine 192 (6), 737-744, 2015 | 53 | 2015 |
| 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 | 47 | 2021 |
| Prevalence and electronic health record-based phenotype of loss-of-function genetic variants in arrhythmogenic right ventricular cardiomyopathy-associated genes ED Carruth, W Young, D Beer, CA James, H Calkins, L Jing, S Raghunath, ... Circulation: Genomic and Precision Medicine 12 (11), e002579, 2019 | 44 | 2019 |
| Noninvasive risk stratification of lung adenocarcinoma using quantitative computed tomography S Raghunath, F Maldonado, S Rajagopalan, RA Karwoski, ZS DePew, ... Journal of Thoracic Oncology 9 (11), 1698-1703, 2014 | 39 | 2014 |
| Quantitative stratification of diffuse parenchymal lung diseases S Raghunath, S Rajagopalan, RA Karwoski, F Maldonado, T Peikert, ... PLoS One 9 (3), e93229, 2014 | 38 | 2014 |
| 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), 36-47, 2022 | 37 | 2022 |
| Short-term automated quantification of radiologic changes in the characterization of idiopathic pulmonary fibrosis versus nonspecific interstitial pneumonia and prediction of … F De Giacomi, S Raghunath, R Karwoski, BJ Bartholmai, T Moua Journal of thoracic imaging 33 (2), 124-131, 2018 | 23 | 2018 |
| Left ventricular and atrial segmentation of 2d echocardiography with convolutional neural networks JV Stough, S Raghunath, X Zhang, JM Pfeifer, BK Fornwalt, CM Haggerty Medical Imaging 2020: Image Processing 11313, 32-38, 2020 | 13 | 2020 |
| Automated quantitative CT versus visual CT scoring in idiopathic pulmonary fibrosis: validation against pulmonary function J Jacob, B Bartholmai, S Rajagopalan, M Kokosi, A Nair, R Karwoski, ... J Thorac Imaging 31 (304), 11, 2016 | 13 | 2016 |
| Computer-aided nodule assessment and risk yield risk management of adenocarcinoma: the future of imaging? F Foley, S Rajagopalan, SM Raghunath, JM Boland, RA Karwoski, ... Seminars in thoracic and cardiovascular surgery 28 (1), 120-126, 2016 | 12 | 2016 |
| Quantitative image analytics for stratified pulmonary medicine S Raghunath, S Rajagopalan, R Karwoski, B Bartholmai, R Robb 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 1779-1782, 2012 | 11 | 2012 |
| Deep neural networks can predict 1-year mortality directly from ECG signal, even when clinically interpreted as normal SM Raghunath, A Ulloa Cerna, L Jing, D Vanmaanen, JV Stough, ... Circulation 140 (Suppl_1), A14425-A14425, 2019 | 9 | 2019 |
