ArticleComputing in cardiology2017
Overcoming Barriers to Quantification and Comparison of Electrocardiographic Imaging Methods: A Community-Based Approach.
Article in Computing in cardiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- A Cardiac Shape Model for Segmentation Uncertainty Quantification.Computing in cardiology · 2021Article
- Uncertainty Quantification of the Effects of Segmentation Variability in ECGI.Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference) · 2021Article
- A Unified Pipeline for ECG Imaging Testing.Computing in cardiology · 2019Article
- Effect of Segmentation Variation on ECG Imaging.Computing in cardiology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
There has been a recent upsurge in the development of electrocardiographic imaging (ECGI) methods, along with a significant increase in clinical application. To better assess the state-of-the-art, enable reliable progress, and facilitate clinical adoption, it is important to be able to compare results in a comprehensive manner, scientifically and clinically. However, studies vary in modeling choices, computational methods, validation mechanisms and metrics, and clinical applications, making unified evaluation and comparison of ECGI a critical challenge. This paper describes initial results of a project to address this challenge via a community-based approach organized by the Consortium for Electrocardiographic Imaging (CEI). We detail different aspects of this collective effort including a data sharing repository, a platform for comparison of different algorithms and modeling approaches on the same datasets, several active workgroups and progress made along these directions. We also summarize the results from groups participating in this collaboration and contributing solutions by applying their methods to the same dataset for comparison.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.