ReviewNature reviews. Cardiology2026
Artificial intelligence-enhanced echocardiography in cardiovascular disease management.
Review in Nature reviews. Cardiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed.
- Point-of-care echocardiography screening for hypertrophic cardiomyopathy using automated deep-learning analysis.European heart journal. Digital health · 2026Article
- Echocardiographic Assessment After Heart Transplant.Diagnostics (Basel, Switzerland) · 2026Review
- Intraprocedural echocardiographic guidance in transcatheter mitral valve interventions: from procedure-specific workflows to integrated multimodal platforms.Journal of cardiovascular imaging · 2026Review
- Artificial intelligence-assisted peri-operative echocardiography: a multicentre observational study.Anaesthesia · 2026Observational
- Artificial Intelligence in Cardiovascular Ultrasound: Clinical Applications, Foundation Models, and the Path to Precision Cardiology.Journal of clinical medicine · 2026Review
- Special article-EchoPeer: a standardized framework for assessing echocardiography reports in the era of artificial intelligence: a recommendation from the Korean Society of Echocardiography AI and Future Strategy Committee.Journal of cardiovascular imaging · 2026Review
- Artificial intelligence in cardiovascular care: a systematic review and meta-analysis of randomised controlled trials.EClinicalMedicine · 2026Article
- A vision transformer deep learning model for assessing pediatric ileocolic intussusception severity using ultrasound images.NPJ digital medicine · 2026Article
- Hierarchical multi-instance learning for targeted triage and classification of common left-to-right shunt lesions from echocardiography videos.BMC medical imaging · 2026Article
- Explainable and Trustworthy Artificial Intelligence in Cardiology: A Narrative Review of Clinical Applications, Operational Integration, and Future Directions.Journal of clinical medicine · 2026Review
- Artificial Intelligence in Cardiac Point-of-Care Ultrasound: A Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Point-of-care echocardiography training pathways: a global perspective and the need for standardisation.Open heart · 2026Review
- Heart disease diagnosis and categorization from ECG signals using hybrid Fuzzy-CNN machine optimized by meta-heuristic algorithms.Scientific reports · 2026Article
- Fully automated artificial intelligence-based echocardiographic analysis substantially reduces workflow time while preserving measurement accuracy: a pilot study.Journal of cardiovascular imaging · 2026Article
- AI-Enabled Precision Echocardiography: Toward Personalized Cardiovascular Care.Diagnostics (Basel, Switzerland) · 2026Review
- EchoVisuALL: From Echocardiography to Gene Discovery.bioRxiv : the preprint server for biology · 2026Article
- Artificial Intelligence-Enabled Echocardiographic Assessment of Right Ventricular Function.medRxiv : the preprint server for health sciences · 2026Article
- AI-Enhanced POCUS in Emergency Care.Diagnostics (Basel, Switzerland) · 2026Review
- Unmasking the Apex: Multimodality Imaging for the Evaluation of Left Ventricular Apical Obliteration.Diagnostics (Basel, Switzerland) · 2026Review
- AI-ECG for Echocardiography Triage in Structural Heart Disease: Evidence, Implementation, and Future Directions.International journal of general medicine · 2026Review
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.
Funding
Abstract
Artificial intelligence (AI) is transforming echocardiography, ushering in an era of improved diagnostic precision, efficiency and patient care. In this Review, we present an in-depth exploration of AI applications in echocardiography, highlighting the latest advances, practical implementations and future directions. We discuss the integration of AI throughout the echocardiographic workflow, from image acquisition and analysis to interpretation. We outline the potential of AI to automate routine measurements and calculations, enable task shifting, recognize disease-specific patterns and uncover new phenogroups that might surpass current diagnostic classifications. Moreover, we address the aspects needed to create trustworthy AI systems, through careful validation, navigating regulatory requirements and upholding ethical standards, thereby presenting a balanced perspective on the advantages and limitations of this rapidly evolving technology. Through an examination of current AI applications, clinical studies and technological breakthroughs, we offer a comprehensive understanding of the evolving role of AI in the future of echocardiography and its capacity to advance cardiovascular care, while also acknowledging the current limitations of the widespread clinical implementation of AI-supported echocardiography.
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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.