Publications — Radcliffe Department of Medicine

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A digital biomarker for aortic stenosis development and progression using deep learning for two-dimensional echocardiography.

Oikonomou EK. et al, (2023)

Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images.

Sangha V. et al, (2023), medRxiv

Severe aortic stenosis detection by deep learning applied to echocardiography.

Holste G. et al, (2023), Eur Heart J

An explainable machine learning-based phenomapping strategy for adaptive predictive enrichment in randomized controlled trials

Oikonomou EK. et al, (2023)

Study Protocol for the Pilot Evaluation for SMartphone-adaptable Artificial Intelligence for PRediction and DeTection of Left Ventricular Systolic Dysfunction (The SMART-LV Pilot Study Protocol)

Dhingra LS. et al, (2023)

Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images

Sangha V. et al, (2023)

CarDS-Plus ECG Platform: Development and Feasibility Evaluation of a Multiplatform Artificial Intelligence Toolkit for Portable and Wearable Device Electrocardiograms

Shankar SV. et al, (2023)

Deep Learning-enabled Detection of Aortic Stenosis from Noisy Single Lead Electrocardiograms

Aminorroaya A. et al, (2023)

Development and Multinational Validation of a Novel Algorithmic Strategy for High Lp(a) Screening

Aminorroaya A. et al, (2023)

Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19.

Kotanidis CP. et al, (2022), Lancet Digit Health, 4, e705 - e716

Biomarkers of Vascular Inflammation for Cardiovascular Risk Prognostication: A Meta-Analysis.

Antonopoulos AS. et al, (2022), JACC Cardiovasc Imaging, 15, 460 - 471

Phenomapping-Derived Tool to Individualize the Effect of Canagliflozin on Cardiovascular Risk in Type 2 Diabetes

Oikonomou EK. et al, (2022), Diabetes Care

Detection of Left Ventricular Systolic Dysfunction from Single-Lead Electrocardiography Adapted for Wearable Devices

Khunte A. et al, (2022)

Multimodality Advanced Cardiovascular and Molecular Imaging for Early Detection and Monitoring of Cancer Therapy-Associated Cardiotoxicity and the Role of Artificial Intelligence and Big Data.

Kwan JM. et al, (2022), Front Cardiovasc Med, 9

The Impact of Induction Therapy on Mortality and Treated Rejection in Cardiac Transplantation: A Retrospective Study

Bellumkonda L. et al, (2022), The Journal of Heart and Lung Transplantation

Effects of canagliflozin on human myocardial redox signalling: clinical implications.

Kondo H. et al, (2021), Eur Heart J, 42, 4947 - 4960

Standardized measurement of coronary inflammation using cardiovascular computed tomography: integration in clinical care as a prognostic medical device.

Oikonomou EK. et al, (2021), Cardiovasc Res, 117, 2677 - 2690

Artificial intelligence in cardiovascular imaging-principles, expectations, and limitations.

Antoniades C. and Oikonomou EK., (2021), Eur Heart J

Association Between Impaired Myocardial Flow Reserve on 82Rubidium Positron Emission Tomography Imaging and Adverse Events in Patients With Autoimmune Rheumatic Disease.

Feher A. et al, (2021), Circ Cardiovasc Imaging, 14

Impaired Myocardial Flow Reserve on 82Rubidium Positron Emission Computed Tomography in Patients with Systemic Sclerosis.

Feher A. et al, (2021), J Rheumatol

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