| 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 | 436 | 2019 |
| 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 | 173 | 2018 |
| Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification A Bratt, J Kim, M Pollie, AN Beecy, NH Tehrani, N Codella, ... Journal of Cardiovascular Magnetic Resonance 21 (1), 1, 2019 | 76 | 2019 |
| Clinical and socioeconomic predictors of heart failure readmissions: a review of contemporary literature A Su, SJ Al'Aref, AN Beecy, JK Min, MG Karas Mayo Clinic Proceedings 94 (7), 1304-1320, 2019 | 54 | 2019 |
| Discharge processes and 30-day readmission rates of patients hospitalized for heart failure on general medicine and cardiology services BM Salata, MR Sterling, AN Beecy, AV Ullal, EC Jones, EM Horn, P Goyal The American journal of cardiology 121 (9), 1076-1080, 2018 | 24 | 2018 |
| A novel deep learning approach for automated diagnosis of acute ischemic infarction on computed tomography AN Beecy, Q Chang, K Anchouche, L Baskaran, K Elmore, K Kolli, ... JACC: Cardiovascular Imaging 11 (11), 1723-1725, 2018 | 20 | 2018 |
| Patterns of scheduled follow-up appointments following hospitalization for heart failure: insights from an urban medical center in the United States P Goyal, MR Sterling, AN Beecy, JT Ruffino, SS Mehta, EC Jones, ... Clinical interventions in aging, 1325-1332, 2016 | 20 | 2016 |
| Risk Reclassification With Coronary Computed Tomography Angiography-Visualized Nonobstructive Coronary Artery Disease According to 2018 American College of Cardiology/American … D Han, A Beecy, K Anchouche, H Gransar, PC Dunham, JH Lee, ... The American journal of cardiology 124 (9), 1397-1405, 2019 | 19 | 2019 |
| Development of novel machine learning model for right ventricular quantification on echocardiography—a multimodality validation study AN Beecy, A Bratt, B Yum, R Sultana, M Das, I Sherifi, RB Devereux, ... Echocardiography 37 (5), 688-697, 2020 | 18 | 2020 |
| Utilizing electronic health data and machine learning for the prediction of 30-day unplanned readmission or all-cause mortality in heart failure AN Beecy, M Gummalla, E Sholle, Z Xu, Y Zhang, K Michalak, K Dolan, ... Cardiovascular Digital Health Journal 1 (2), 71-79, 2020 | 12 | 2020 |
| Leveraging deep representations of radiology reports in survival analysis for predicting heart failure patient mortality HG Lee, E Sholle, A Beecy, S Al’Aref, Y Peng Proceedings of the conference. Association for Computational Linguistics …, 2021 | 7 | 2021 |
| Implications of bias in artificial intelligence: considerations for cardiovascular imaging M van Assen, A Beecy, G Gershon, J Newsome, H Trivedi, J Gichoya Current Atherosclerosis Reports 26 (4), 91-102, 2024 | 4 | 2024 |
| Using electronic health records for population health sciences: a case study to evaluate the associations between changes in left ventricular ejection fraction and the built … Y Zhang, M Tayarani, SJ Al’Aref, AN Beecy, Y Liu, E Sholle, ... JAMIA open 3 (3), 386-394, 2020 | 4 | 2020 |
| Artificial Intelligence for Cardiovascular Care—Part 1: Advances: JACC Review Topic of the Week P Elias, SS Jain, T Poterucha, M Randazzo, FL Jimenez, R Khera, ... Journal of the American College of Cardiology 83 (24), 2472-2486, 2024 | 3 | 2024 |
| Association between epicardial fat volume and fractional flow reserve: an analysis of the determination of fractional flow reserve (DeFACTO) study A Beecy, BÓ Hartaigh, J Schulman-Marcus, K Anchouche, H Gransar, ... Clinical Imaging 51, 30-34, 2018 | 3 | 2018 |
| Preparing for the bedside—optimizing a postpartum depression risk prediction model for clinical implementation in a health system Y Liu, R Joly, M Reading Turchioe, N Benda, A Hermann, A Beecy, ... Journal of the American Medical Informatics Association 31 (6), 1258-1267, 2024 | 1 | 2024 |
| EchoNext: An ECG-Based Deep Learning Model to Detect Structural Heart Disease L Jing, J Finer, D Hartzel, C Kelsey, D Rocha, J Ruhl, A Volodarskiy, ... Circulation 148 (Suppl_1), A14647-A14647, 2023 | 1 | 2023 |
| A novel deep learning approach for automated diagnosis of cerebral infarction on computed tomography A Knight-Greenfield, A Beecy, Q Chang, K Anchouche, L Baskaran, ... STROKE 49, 2018 | 1 | 2018 |
| Strengthening the use of artificial intelligence within healthcare delivery organizations: balancing regulatory compliance and patient safety MP Sendak, VX Liu, A Beecy, DE Vidal, K Shaw, MA Lifson, D Tobey, ... Journal of the American Medical Informatics Association 31 (7), 1622-1627, 2024 | | 2024 |
| Implementing AI models in clinical workflows: a roadmap F Wang, A Beecy BMJ Evidence-Based Medicine, 2024 | | 2024 |
