| Tolvaptan for heart failure, systematic review and meta-analysis of trials E Alskaf, A Tridente, A Al-Mohammad Journal of cardiovascular pharmacology 68 (3), 196-203, 2016 | 27 | 2016 |
| Mesalazine-induced lung fibrosis E Alskaf, A Aljoudeh, F Edenborough Case Reports 2013, bcr2013008724, 2013 | 16 | 2013 |
| The mystery of defining aortic valve area: what have we learnt from three-dimensional imaging modalities? E Alskaf, A Kardos Journal of Echocardiography 16, 130-138, 2018 | 13 | 2018 |
| Brief research report: quantitative analysis of potential coronary microvascular disease in suspected long-COVID syndrome P Doeblin, F Steinbeis, CM Scannell, C Goetze, S Al-Tabatabaee, J Erley, ... Frontiers in Cardiovascular Medicine 9, 877416, 2022 | 12 | 2022 |
| Left atrial ejection fraction estimation using SEGANet for fully automated segmentation of CINE MRI A Lourenço, E Kerfoot, C Dibblin, E Alskaf, M Anjari, AA Bharath, AP King, ... Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC …, 2021 | 12 | 2021 |
| Physics-informed self-supervised deep learning reconstruction for accelerated first-pass perfusion cardiac MRI E Martín-González, E Alskaf, A Chiribiri, P Casaseca-de-la-Higuera, ... International workshop on machine learning for medical image reconstruction …, 2021 | 7 | 2021 |
| AI-AIF: artificial intelligence-based arterial input function for quantitative stress perfusion cardiac magnetic resonance CM Scannell, E Alskaf, N Sharrack, R Razavi, S Ourselin, AA Young, ... European Heart Journal-Digital Health 4 (1), 12-21, 2023 | 6 | 2023 |
| Deep learning applications in myocardial perfusion imaging, a systematic review and meta-analysis E Alskaf, U Dutta, CM Scannell, A Chiribiri Informatics in Medicine Unlocked 32, 101055, 2022 | 6 | 2022 |
| High-resolution free-breathing quantitative first-pass perfusion cardiac MR using dual-echo Dixon with spatio-temporal acceleration J Tourais, CM Scannell, T Schneider, E Alskaf, R Crawley, F Bosio, ... Frontiers in Cardiovascular Medicine 9, 884221, 2022 | 4 | 2022 |
| Deep learning applications in coronary anatomy imaging: a systematic review and meta-analysis E Alskaf, U Dutta, CM Scannell, A Chiribiri Journal of medical artificial intelligence 5, 11, 2022 | 2 | 2022 |
| High-resolution free-breathing automated quantitative myocardial perfusion by cardiovascular magnetic resonance for the detection of functionally significant coronary artery … R Crawley, KP Kunze, X Milidonis, J Highton, S McElroy, SM Frey, ... European heart journal. Cardiovascular Imaging, jeae084, 2024 | 1 | 2024 |
| 29 AI-AIF: artificial intelligence-based arterial input function correction for quantitative stress perfusion cardiac magnetic resonance CM Scannell, E Alskaf, N Sharrack, S Plein, A Chribri Heart 108 (Suppl 3), A25-A26, 2022 | 1 | 2022 |
| The impact of dark-blood versus conventional bright-blood late gadolinium enhancement on the myocardial ischemic burden R Franks, RJ Holtackers, E Alskaf, MS Nazir, B Clapp, JE Wildberger, ... European Journal of Radiology 144, 109947, 2021 | 1 | 2021 |
| Aortic valve area using computed tomography‐derived correction factor to improve the validity of left ventricular outflow tract measurements E Alskaf, T Gupta, A Kardos Echocardiography 37 (2), 196-206, 2020 | 1 | 2020 |
| What is the Logic behind Treating Some Heart Failure Patients without ACE Inhibitors and Beta-Blockers E Alskaf, S Ahmed, D Barnett, M Warriner, A Birchall, V Watt, ... J Pharmacogenomics Pharmacoproteomics 5 (137), 2153-0645.1000137, 2014 | 1 | 2014 |
| REVISITING THE UTILITY OF LATE GADOLINIUM ENHANCEMENT TO PREDICT SEGMENTAL RECOVERY IN ISCHEMIC VENTRICULAR DYSFUNCTION: SECONDARY ANALYSIS OF THE REVIVEDBCIS2 RANDOMISED TRIAL M Ryan, H Morgan, S Nazir, PG Masci, M Dodd, J Mancio, E Alskaf, ... Journal of the American College of Cardiology 83 (13_Supplement), 1358-1358, 2024 | | 2024 |
| QUALITATIVE AMERICAN HEART ASSOCIATION PLOT OF LATE GADOLINIUM ENHANCEMENT FOR MORTALITY AND VENTRICULAR ARRHYTHMIA PREDICTION USING ARTIFICIAL INTELLIGENCE E Alskaf, C Scannell, A Suinesiaputra, A Young, D Perera, A Chiribiri Journal of the American College of Cardiology 83 (13_Supplement), 2583-2583, 2024 | | 2024 |
| Hybrid artificial intelligence outcome prediction using features extraction from stress perfusion cardiac magnetic resonance images and electronic health records E Alskaf, R Crawley, CM Scannell, A Suinesiaputra, A Young, PG Masci, ... Journal of medical artificial intelligence 7, 2024 | | 2024 |
| Assessment of the Effect of Patient Age and Sex on Normal Hyperemic and Baseline Myocardial Blood Flow and Myocardial Perfusion Reserve Using High-resolution Inline … R Crawley, X Milidonis, K Kunze, J Highton, S Frey, D Hoefler, ... Journal of Cardiovascular Magnetic Resonance 26, 2024 | | 2024 |
| Accurate Measurement of Myocardial Blood Flow in Atrial Fibrillation Using a High-resolution Stress Perfusion Sequence with Automated Inline Quantified Perfusion Mapping R Crawley, X Milidonis, K Kunze, J Highton, S Frey, D Hoefler, ... Journal of Cardiovascular Magnetic Resonance 26, 2024 | | 2024 |
