ArticleFrontiers in cardiovascular medicine2021
Automated Quality-Controlled Cardiovascular Magnetic Resonance Pericardial Fat Quantification Using a Convolutional Neural Network in the UK Biobank.
Article in Frontiers in cardiovascular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 25 citations in OpenAlex.
- Brain-heart-eye axis revealed by multi-organ imaging genetics and proteomics.Nature biomedical engineering · 2026Article
- Association of pericardial fat volume with risk of incident type 2 diabetes mellitus or major adverse cardiovascular events: Evidence from UK Biobank cohort study.Nutrition & metabolism · 2026Article
- Sex-specific associations of physical frailty with cardiac structure and function: a cross-sectional study based on UK Biobank.BMC cardiovascular disorders · 2026Article
- Cross-organ analysis reveals associations between vascular properties of the retina, the carotid and aortic arteries, and the brain.Communications medicine · 2026Article
- Associations between accelerometer-measured physical activity, sedentary behaviour and pericardial adiposity: a prospective cohort study of UK Biobank participants.BMJ public health · 2026Article
- Genome-Wide Association Study of Pericardial Fat Area in 28 161 UK Biobank Participants.Journal of the American Heart Association · 2023Article
- Multilevel comparison of deep learning models for function quantification in cardiovascular magnetic resonance: On the redundancy of architectural variations.Frontiers in cardiovascular medicine · 2023Article
- Machine learning of adipose tissue in atrial fibrillation.Heart rhythm · 2022Article
- Pericardial adiposity is independently linked to adverse cardiovascular phenotypes: a CMR study of 42 598 UK Biobank participants.European heart journal. Cardiovascular Imaging · 2022Article
- A Survey on the Role of Artificial Intelligence in Biobanking Studies: A Systematic Review.Diagnostics (Basel, Switzerland) · 2022Review
- Deep-Learning Segmentation of Epicardial Adipose Tissue Using Four-Chamber Cardiac Magnetic Resonance Imaging.Diagnostics (Basel, Switzerland) · 2022Article
- Clinician's guide to trustworthy and responsible artificial intelligence in cardiovascular imaging.Frontiers in cardiovascular medicine · 2022Review
- Cardiac MR: From Theory to Practice.Frontiers in cardiovascular medicine · 2022Review
- Epicardial Fat Expansion in Diabetic and Obese Patients With Heart Failure and Preserved Ejection Fraction-A Specific HFpEF Phenotype.Frontiers in cardiovascular medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 7 institutions in 2 countries.
Funding
Abstract
PubMed holds no abstract for this paper.
Indexed as
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.