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Prashanthan Sanders

dblp:06/9537 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics
cardiac electrophysiology
0.212016
Quantitative-Electrogram-Based Methods for Guiding Catheter Ablation in Atrial Fibrillation · Proc. IEEE 2016

Methods — techniques the papers use, named apart from their topics

quantitative signal processing · 0.2
YearPublicationVenuePosition
2016 Quantitative-Electrogram-Based Methods for Guiding Catheter Ablation in Atrial Fibrillation
abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia in humans, with an estimated lifetime prevalence of 25%. It is characterized by irregular and disorganized electrical activation of the atria. In the past decade, catheter ablation, i.e., focally burning targeted areas of cardiac muscle, has emerged as a potentially curative therapy for AF. Accompanying this development there has been an increasing interest in quantitative intraprocedural signal analysis to guide the selection of ablation targets. In this review, we provide an overview of quantitative signal processing approaches for mapping and ablation of AF.
Mathias Baumert, Prashanthan Sanders, Anand N. Ganesan
Proc. IEEE2