2025
npj Digital Medicine
Deriving novel atrial fibrillation phenotypes using a tree-based artificial
intelligence-enhanced
electrocardiography approach
Mehak Gurnani, Konstantinos Patlatzoglou, Joseph Barker, Libor
Pastika, Boroumand Zeidaabadi, Ibrahim Antoun, Riyaz Somani, ... Arunashis Sau, Fu Siong Ng
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2025
npj Digital Medicine
The cost of explainability in artificial intelligence-enhanced electrocardiogram models
Konstantinos Patlatzoglou, Libor Pastika, Joseph Barker, Ewa
Sieliwonczyk, Gul Rukh Khattak, Boroumand Zeidaabadi, Antônio H Ribeiro, ... Arunashis Sau, Fu
Siong Ng
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2025
Heart Rhythm
Image based artificial intelligence-enhanced ECG prediction of incident atrial fibrillation
Boroumand Zeidaabadi, Konstantinos Patlatzoglou, Joseph Barker, Libor
Pastika, Gul Rukh Khattak, Mehak Gurnani, Xavier Da Silva Anjos Machado et al.
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2025
Heart Rhythm
Prediction of incident atrial fibrillation: A comprehensive evaluation of conventional and
artificial intelligence-enhanced approaches
Arunashis Sau, Ewa Sieliwonczyk, Joseph Barker,
Boroumand Zeidaabadi, Libor Pastika, Konstantinos Patlatzoglou, Gul Rukh Khattak et al.
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2025
JAMA Cardiology
Artificial Intelligence–Enhanced Electrocardiography for Complete Heart Block Risk
Stratification
Arunashis Sau, Henry Zhang, Joseph Barker,
Libor Pastika, Konstantinos Patlatzoglou et al.
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2025
European Heart Journal
Artificial intelligence-enhanced electrocardiography to predict regurgitant valvular heart
diseases: an international study
Yixiu Liang , Arunashis Sau , Boroumand Zeidaabadi , Joseph
Barker , Konstantinos Patlatzoglou , Libor Pastika , Ewa Sieliwonczyk , Zachary
Whinnett , Nicholas S Peters et al.
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2025
Journal of the American Heart Association
Revisiting Abnormalities of Ventricular Depolarization: Redefining Phenotypes and Associated
Outcomes Using Tree‐Based Dimensionality Reduction
Mehak Gurnani, Konstantinos Patlatzoglou, Joseph Barker, Derek
Bivona, Libor Pastika et al.
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2025
Heart Rhythm O2
Granger causality connectivity analysis of persistent atrial fibrillation dynamics reveals
posterior wall mechanistic insights
Joseph Barker, Arunashis Sau, Nikesh Bajaj, Alex Jenkins et al.
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2024
The Lancet Digital Health
Artificial intelligence-enhanced electrocardiography for the identification of a sex-related
cardiovascular risk continuum
Sau, A, Sieliwonczyk, E, Patlatzoglou, K, Pastika, L, McGurk, A,
Ribeiro, A.H. et al.
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Paper
2024
JAMA Cardiology
Artificial Intelligence–Enhanced Electrocardiography for Prediction of Incident Hypertension
Sau, A, Barker, J, Pastika, L et al.
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2024
The Lancet Digital Health
Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk
estimation: a model development and validation study
Arunashis Sau, Libor Pastika, Ewa Sieliwonczyk, Konstantinos
Patlatzoglou, Antônio H Ribeiro et al.
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2024
European Heart Journal - Digital Health
A comparison of artificial intelligence-enhanced electrocardiography approaches for prediction
of time-to-mortality using electrocardiogram images
Arunashis Sau, Boroumand Zeidaabadi, Konstantinos Patlatzoglou, Libor
Pastika, et al.
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Paper
2024
JACC: Case Reports
Smartwatch Locates Myocardial Lesion in Stable Angina
Boroumand Zeidaabadi, Joseph Barker, Libor Pastika, Nickolaos
Pantazopoulos, Raffi Kaprielian, Fu Siong Ng.
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Paper
2024
npj Digital Medicine
Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of
future cardiometabolic disease
Pastika, L., Sau, A., Patlatzoglou, K. et al.
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Paper
2023
BMJ Medicine
The emerging role of artificial intelligence enabled electrocardiograms in healthcare
Sau A, Ng FS.
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2023
European Heart Journal Digital Health
Machine learning-derived cycle length variability metrics predict spontaneously terminating
ventricular tachycardia in implantable cardioverter defibrillator recipients
Sau A, Ahmed A, Chen JY, Pastika L, Wright I, Li X, et al.
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Paper
2023
Cardiovascular Digital Health Journal
Artificial intelligence-enabled electrocardiogram to distinguish atrioventricular re-entrant
tachycardia from atrioventricular nodal re-entrant tachycardia
Sau A, Ibrahim S, Kramer DB, Waks JW, et al.
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Paper
2022
European Heart Journal Digital Health
Artificial intelligence-enabled electrocardiogram to distinguish cavotricuspid isthmus
dependence from other atrial tachycardia mechanisms
Sau A, Ibrahim S, Ahmed A, Handa B, et al.
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2022
Cardiovascular Digital Health Journal
Is machine learning the future for atrial fibrillation screening?
Sivanandarajah P, Wu H, Bajaj N, Khan S, Ng FS.
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2022
Nature Scientific Reports
A fully-automated paper ECG digitisation algorithm using deep learning
Wu H, Patel KHK, Li X, Zhang B, et al.
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