Demo Data from SIGIR 2026 / reviewers in the wild / expert
Prashanthan Sanders
dblp:06/9537
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics
cardiac electrophysiology |
0.2 | 1 | 2016 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Quantitative-Electrogram-Based Methods for Guiding Catheter Ablation in Atrial FibrillationabstractAtrial 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. IEEE | 2 |