ArticleHeart rhythm O22020
Symmetric Projection Attractor Reconstruction analysis of murine electrocardiograms: Retrospective prediction of Scn5a
Article in Heart rhythm O2, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- Classification of paroxysmal atrial fibrillation using sinus rhythm electrocardiograms using the symmetric projection attractor reconstruction method.Scientific reports · 2026Article
- Artificial intelligence for Brugada syndrome diagnosis and gene variants interpretation.American journal of cardiovascular disease · 2025Review
- Article
- DeepMiceTL: a deep transfer learning based prediction of mice cardiac conduction diseases using early electrocardiograms.Briefings in bioinformatics · 2023Article
- Detecting paroxysmal atrial fibrillation from normal sinus rhythm in equine athletes using Symmetric Projection Attractor Reconstruction and machine learning.Cardiovascular digital health journal · 2022Article
- Symmetric Projection Attractor Reconstruction: Sex Differences in the ECG.Frontiers in cardiovascular medicine · 2021Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLife-threatening arrhythmias resulting from genetic mutations are often missed in current electrocardiogram (ECG) analysis. We combined a new method for ECG analysis that uses all the waveform data with machine learning to improve detection of such mutations from short ECG signals in a mouse model.
objectiveWe sought to detect consequences of Na
methodsLead I and II ECG signals from anesthetized wild-type and Scn5a
resultsClassification of genotype using the attractor features gave higher accuracy than using either the ECG intervals or the intervals and amplitudes. However, the highest accuracy (96%) was obtained using all the features. Accuracies for different subgroups of the data were obtained and compared.
conclusionDetection of the Scn5a
Indexed as
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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.