ArticleScientific reports2022
Author Correction: Deep learning of ECG waveforms for diagnosis of heart failure with a reduced left ventricular ejection fraction.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07636759 (Prospective Observational Cohort Study of Deep Learning-based ECG Algorithm for Detecting Left Ventricular Systolic Dysfunction), which is not on this map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Prospective Observational Cohort Study of Deep Learning-based ECG Algorithm for Detecting Left Ventricular Systolic Dysfunction
Who cites it
1 citing paper in PubMed.
- Deep learning algorithm for detection of acute heart failure using standard ECG waveforms.European heart journal. Digital health · 2026Article
Corrections and comments
- Erratum for
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.