Summary
Dr Sau is a clinical research fellow and cardiology registrar currently undertaking a PhD under the supervision of Dr Fu Siong Ng, Prof Nicholas S Peters and Prof Danilo Mandic.
Dr Sau’s main research interest is the application of machine learning to further the field of cardiology, including applying deep learning to the surface ECG and to intracardiac electrograms.
His work on AI-ECG derived phenogroups was awarded first prize at the British Cardiovascular Society/British Heart Foundation/British Atherosclerosis Society/British Society of Cardiovascular Research Young Investigator Award 2023
He studied medicine at Imperial College London, where he was awarded a First Class (Hon) BSc degree in Medical Sciences with Cardiovascular sciences and Distinctions in Medical Sciences, Clinical Science and Clinical Practice. He has been awarded a Postgraduate Certificate in Medical Education by the University of Dundee.
His postgraduate clinical training to date has been in the North West Thames deanery, most recently as an NIHR Academic Clinical Fellow. During his ST4 year he was awarded a British Heart Foundation Clinical Research Training Fellowship and started this in October 2021.
Dr Sau maintains a strong interest in clinical electrophysiology and is an aspiring cardiac electrophysiologist.
Publications
Journals
Sau A, Kapadia S, Al-Aidarous S, et al., 2023, Temporal trends and lesion sets for persistent atrial fibrillation ablation: a meta-analysis with trial sequential analysis and meta-regression, Circulation: Arrhythmia and Electrophysiology, ISSN:1941-3084
Sau A, Amoiradaki K, Ardissino M, et al., 2023, British Cardiovascular Society/British Heart Foundation/British Atherosclerosis Society/British Society for Cardiovascular Research Young Investigator Award 2023., Heart
Sau A, Pastika L, Ng FS, 2023, Atrial fibrillation phenotypes: the route to personalised care?, Heart
Sau A, Ng FS, 2023, Response to letter by Saumarez et al. entitled 'Regarding the editorial by Sau and Ng. "Hypertrophic cardiomyopathy risk stratification based on clinical or dynamic electrophysiological features: two sides of the same coin"'., Europace, Vol:25
Sau A, Ng FS, Sau A, 2023, The emerging role of artificial intelligence-enabled electrocardiograms in healthcare, Bmj Medicine, ISSN:2754-0413