Yingjing FengUniversity of Birmingham · Centre for Systems Modelling and Quantitative Biomedicine
Yingjing Feng
PhD
Postdoctoral Research Fellow at Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham
About
12
Publications
4,697
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449
Citations
Introduction
Additional affiliations
September 2015 - September 2016
Position
- Master's Student
Description
- I finished my Master in Computing (Machine Learning) degree and conducted my Master's project on "An Efficient Cardiac Mapping Strategy for Radiofrequency Catheter Ablation with Active Learning", which was published in IJCARS journeal.
Education
May 2018 - December 2021
September 2015 - September 2016
Independent Researcher
Field of study
- Computing (Machine Learning)
Publications
Publications (12)
Objective: About half of patients experience recurrence of atrial fibrillation (AF) within three to five years after a single catheter ablation procedure. The suboptimality of the long-term outcomes likely results from the inter-patient variability of AF mechanisms, which can be remedied by improved patient screening. We aim to improve the interpre...
Focal sources (FS) are believed to be important triggers and a perpetuation mechanism for paroxysmal atrial fibrillation (AF). Detecting FS and determining AF sustainability in atrial tissue can help guide ablation targeting. We hypothesized that sustained rotors during FS-driven episodes indicate an arrhythmogenic substrate for sustained AF, and t...
Atrial fibrillation (AF), the rapid and irregular activation of the atria, is the most common clinical arrhythmia. Catheter ablation therapy is the most effective treatment and improves the quality of life, but standard protocols show sub-optimal long-term success, substantiating the need for personalized ablation. Body surface potential maps (BSPM...
Reliable patient-specific ventricular repolarization times (RTs) can identify regions of functional block or afterdepolarizations, indicating arrhythmogenic cardiac tissue and the risk of sudden cardiac death. Unipolar electrograms (UEs) record electric potentials, and the Wyatt method has been shown to be accurate for estimating RT from a UE. High...
Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twi...
Objective
A major challenge in radiofrequency catheter ablation procedures is the voltage and activation mapping of the endocardium, given a limited mapping time. By learning from expert interventional electrophysiologists (operators), while also making use of an active-learning framework, guidance on performing cardiac voltage mapping can be provi...