ArticleNature communications2025
Self-supervised learning for label-free segmentation in cardiac ultrasound.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Imaging-anchored multiomics in cardiovascular disease: integrating cardiac imaging, bulk, single-cell, and spatial transcriptomics.Briefings in bioinformatics · 2026Review
- Automated Extraction of Pulsatile Stiffness and Wall Asymmetry from Aortic M-Mode Ultrasound Images.Bioengineering (Basel, Switzerland) · 2026Article
- Generative deep learning for foundational video translation in ultrasound.Scientific reports · 2026Article
- EchoVisuALL: From Echocardiography to Gene Discovery.bioRxiv : the preprint server for biology · 2026Article
- Synthetic X‑ray‑driven tracking and control of miniature medical devices.Nature machine intelligence · 2026Article
- Are AI Foundation Models Efficient for Segmentation of Echocardiograms?Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography · 2025Article
- Article
- ChatGPT Helped Me Write This Talk Title, but Can It Read an Echocardiogram?Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography · 2023Article
- Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient Care.JACC. Cardiovascular imaging · 2023Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Segmentation and measurement of cardiac chambers from ultrasound is critical, but laborious and poorly reproducible. Neural networks can assist, but supervised approaches require the same problematic manual annotations. We build a pipeline for self-supervised segmentation combining computer vision, clinical knowledge, and deep learning. We train on 450 echocardiograms and test on 18,423 echocardiograms (including external data), using the resulting segmentations to calculate measurements. Coefficient of determination (r
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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.