| Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease L Pastika, A Sau, K Patlatzoglou, E Sieliwonczyk, AH Ribeiro, KA McGurk, ... npj Digital Medicine 7 (1), 167, 2024 | 5 | 2024 |
| Deep neural networks for automatic classification of anesthetic-induced unconsciousness K Patlatzoglou, S Chennu, M Boly, Q Noirhomme, V Bonhomme, ... Brain Informatics: International Conference, BI 2018, Arlington, TX, USA …, 2018 | 5 | 2018 |
| Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study A Sau, L Pastika, E Sieliwonczyk, K Patlatzoglou, AH Ribeiro, KA McGurk, ... The Lancet Digital Health 6 (11), e791-e802, 2024 | 4 | 2024 |
| Generalized prediction of unconsciousness during propofol anesthesia using 3D convolutional neural networks K Patlatzoglou, S Chennu, O Gosseries, V Bonhomme, A Wolff, S Laureys 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 4 | 2020 |
| Prognostic significance and associations of neural network–derived electrocardiographic features A Sau, AH Ribeiro, KA McGurk, L Pastika, N Bajaj, M Gurnani, ... Circulation: Cardiovascular Quality and Outcomes 17 (12), e010602, 2024 | 3 | 2024 |
| Artificial Intelligence–Enhanced Electrocardiography for Prediction of Incident Hypertension A Sau, J Barker, L Pastika, E Sieliwonczyk, K Patlatzoglou, KA McGurk, ... JAMA cardiology, 2025 | 1 | 2025 |
| Deep Learning for Electrophysiological Investigation and Estimation of Anesthetic-Induced Unconsciousness K Patlatzoglou University of Kent, 2022 | 1 | 2022 |
| A comparison of artificial intelligence–enhanced electrocardiography approaches for the prediction of time to mortality using electrocardiogram images A Sau, B Zeidaabadi, K Patlatzoglou, L Pastika, AH Ribeiro, E Sabino, ... European Heart Journal-Digital Health, ztae090, 2024 | | 2024 |
| Machine Learning of ECG Waveforms for Outcomes After Left Bundle Branch Area Pacing in Heart Failure K Bilchick, D Bivona, K Patlatzoglou, FS Ng, K Ellenbogen, A Pillai Circulation 150 (Suppl_1), A4140782-A4140782, 2024 | | 2024 |
| Artificial Intelligence-Enabled Electrocardiography For The Prediction of Future Type 2 Diabetes Mellitus L Pastika, K Patlatzoglou, E Sieliwonczyk, J Barker, B Zeidaabadi, ... Circulation 150 (Suppl_1), A4137169-A4137169, 2024 | | 2024 |
| Unsupervised feature extraction using deep learning empowers discovery of genetic determinants of the electrocardiogram E Sieliwonczyk, A Sau, K Patlatzoglou, KA McGurk, L Pastika, PK Thami, ... medRxiv, 2024.10. 07.24314993, 2024 | | 2024 |
| Prediction of mortality, future arrhythmia and cardiovascular disease: an artificial intelligence-enhanced electrocardiography platform A Sau, L Pastika, E Sieliwonczyk, K Patlatzoglou, AH Ribeiro, K Mcgurk, ... European Heart Journal 45 (Supplement_1), ehae666. 3474, 2024 | | 2024 |
| Unsupervised electrocardiogram feature extraction using deep learning empowers discovery of genetic and phenotypic determinants of cardiac electrophysiology E Sieliwonczyk, A Sau, K Patlatzoglou, K Mcgurk, L Pastika, P Thami, ... European Heart Journal 45 (Supplement_1), ehae666. 3441, 2024 | | 2024 |
| Digitisation of electrocardiographic images enable artificial intelligence-based mortality prediction K Patlatzoglou, A Sau, B Zeidaabadi, L Pastika, N Peters, D Kramer, ... European Heart Journal 45 (Supplement_1), ehae666. 3473, 2024 | | 2024 |
| Siamese neural networks can identify subjects from anonymised ECGs K Macierzanka, A Sau, K Patlatzoglou, L Pastika, E Sieliwonczyk, ... European Heart Journal 45 (Supplement_1), ehae666. 3460, 2024 | | 2024 |
| Artificial intelligence-enhanced electrocardiography predicts 10-year risk of atherosclerotic cardiovascular disease H Zhang, A Sau, K Patlatzoglou, L Pastika, E Sieliwonczyk, M Gurnani, ... European Heart Journal 45 (Supplement_1), ehae666. 3499, 2024 | | 2024 |
| Sex related cardiovascular risk is non-dichotomous: artificial intelligence enhanced electrocardiography reveals continuum of risk in females A Sau, E Sieliwonczyk, K Patlatzoglou, L Pastika, K Mcgurk, AH Ribeiro, ... European Heart Journal 45 (Supplement_1), ehae666. 3462, 2024 | | 2024 |
| Utilizing unsupervised machine learning to uncover novel phenogroups within the broad QRS complex M Gurnani, A Sau, K Patlatzoglou, J Barker, L Pastika, NS Peters, ... European Heart Journal 45 (Supplement_1), ehae666. 333, 2024 | | 2024 |
| Accurate detection of dilated cardiomyopathy onset through machine learning predictions from ECG data E Sieliwonczyk, A Sau, Y Liang, K Patlatzoglou, K Mcgurk, E Jennings, ... European Heart Journal 45 (Supplement_1), ehae666. 956, 2024 | | 2024 |
| 224 An actionable, explainable, and biologically plausible AI-ECG risk estimation platform for diabetes mellitus L Pastika, A Sau, E Sieliwonczyk, K Patlatzoglou, KA McGurk, S Khan, ... Heart 110 (Suppl 3), A232-A232, 2024 | | 2024 |
Fu Siong NgImperial College LondonE-mail megerősítve itt: imperial.ac.uk