| Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging SJ Al’Aref, K Anchouche, G Singh, PJ Slomka, KK Kolli, A Kumar, ... European heart journal 40 (24), 1975-1986, 2019 | 498 | 2019 |
| Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography … SJ Al’Aref, G Maliakal, G Singh, AR van Rosendael, X Ma, Z Xu, ... European heart journal 41 (3), 359-367, 2020 | 206 | 2020 |
| Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry AR van Rosendael, G Maliakal, KK Kolli, A Beecy, SJ Al’Aref, A Dwivedi, ... Journal of cardiovascular computed tomography 12 (3), 204-209, 2018 | 177 | 2018 |
| Machine learning in cardiac CT: basic concepts and contemporary data G Singh, SJ Al’Aref, M Van Assen, TS Kim, A van Rosendael, KK Kolli, ... Journal of Cardiovascular Computed Tomography 12 (3), 192-201, 2018 | 124 | 2018 |
| Human activity recognition using binary motion image and deep learning T Dobhal, V Shitole, G Thomas, G Navada Procedia computer science 58, 178-185, 2015 | 95 | 2015 |
| Determinants of in‐hospital mortality after percutaneous coronary intervention: a machine learning approach SJ Al'Aref, G Singh, AR van Rosendael, KK Kolli, X Ma, G Maliakal, ... Journal of the American Heart Association 8 (5), e011160, 2019 | 93 | 2019 |
| Identification and quantification of cardiovascular structures from CCTA: an end-to-end, rapid, pixel-wise, deep-learning method L Baskaran, G Maliakal, SJ Al’Aref, G Singh, Z Xu, K Michalak, K Dolan, ... Cardiovascular Imaging 13 (5), 1163-1171, 2020 | 73 | 2020 |
| A boosted ensemble algorithm for determination of plaque stability in high-risk patients on coronary CTA SJ Al’Aref, G Singh, JW Choi, Z Xu, G Maliakal, AR van Rosendael, ... Cardiovascular Imaging 13 (10), 2162-2173, 2020 | 49 | 2020 |
| Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning L Baskaran, SJ Al’Aref, G Maliakal, BC Lee, Z Xu, JW Choi, SE Lee, ... PloS one 15 (5), e0232573, 2020 | 49 | 2020 |
| Sparse-view cone beam CT reconstruction using data-consistent supervised and adversarial learning from scarce training data A Lahiri, G Maliakal, ML Klasky, JA Fessler, S Ravishankar IEEE Transactions on Computational Imaging 9, 13-28, 2023 | 28 | 2023 |
| Extraction of radiographic findings from unstructured thoracoabdominal computed tomography reports using convolutional neural network based natural language processing M Pandey, Z Xu, E Sholle, G Maliakal, G Singh, Z Fatima, D Larine, ... PLoS One 15 (7), e0236827, 2020 | 25 | 2020 |
| Deep learning based automatic segmentation of cardiac computed tomography G Singh, S Alaref, G Maliakal, M Pandey, A van Rosendael, B Lee, ... Journal of the American College of Cardiology 73 (9S1), 1643-1643, 2019 | 6 | 2019 |
| Deep reinforcement learning based unrolling network for mri reconstruction C Wang, R Zhang, G Maliakal, S Ravishankar, B Wen 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-5, 2023 | 5 | 2023 |
| Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortium FY Lin, BP Goebel, BC Lee, Y Lu, L Baskaran, YE Yoon, GT Maliakal, ... Journal of cardiovascular computed tomography 17 (1), 28-33, 2023 | 3 | 2023 |
| Data from: Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning L Baskaran, SJ Al’Aref, G Maliakal, BC Lee, Z Xu, JW Choi, SE Lee, ... Borealis, 2021 | 2 | 2021 |
| AGE CAC INTERACTION WITH 10-YEAR CV MORTALITY USING MODEL-AGNOSTIC INTERPRETATION OF MACHINE LEARNING: THE CAC CONSORTIUM B Goebel, BC Lee, Y Lu, Y Yoon, L Baskaran, G Maliakal, U Gianni, ... Journal of the American College of Cardiology 77 (18_Supplement_1), 3232-3232, 2021 | | 2021 |
| Integrated Cross-Sectional Modeling for the Prediction of 30-Day Unplanned Readmissions or All-Cause Mortality in Primary Heart Failure SJ Al’Aref, Z Xu, M Gummalla, E Sholle, Y Zhang, RM Creber, Y Zhang, ... Circulation 140 (Suppl_1), A14873-A14873, 2019 | | 2019 |
| Comparing a Novel Machine Learning Method to the Martin-Hopkins Equation for Low-Density Lipoprotein Cholesterol Estimation for Levels Below 70 Mg/dl Y Hussain, G Singh, Z Xu, E Sholle, K Michalak, K Dolan, G Maliakal, ... Circulation 140 (Suppl_1), A13842-A13842, 2019 | | 2019 |
| TCT-55 Clinical Predictors of Obstructive Coronary Artery Disease in Individuals with Suspected Coronary Artery Disease S Al'Aref, A van Rosendael, G Maliakal, G Singh, X Ma, M Pandey, ... Journal of the American College of Cardiology 72 (13S), B24-B25, 2018 | | 2018 |
| A NOVEL ENSEMBLE MACHINE LEARNING-BASED METHOD VERSUS CLINICAL RISK SCORING FOR DISCRIMINATION OF INDIVIDUALS WHO WILL VERSUS WILL NOT EXPERIENCE ACUTE CORONARY SYNDROME AFTER … S Al’Aref, G Maliakal, M Cheng, K Kolli, G Singh, M Pandey, A Kumar, ... Journal of the American College of Cardiology 71 (11S), A1628-A1628, 2018 | | 2018 |