ReviewJournal of cardiovascular development and disease2025
The Role of Artificial Intelligence in Cardiac Amyloidosis: A Focus on Diagnosis and Clinical Application.
Review in Journal of cardiovascular development and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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
4 citing papers in PubMed.
- Automated identification of cardiac amyloidosis using cross-modal neural networks on [Formula: see text]-Pyrophosphate SPECT imaging and clinical data.The international journal of cardiovascular imaging · 2026Article
- Subtype specific artificial intelligence modelling of cardiac amyloidosis using echocardiography and electrocardiography.European heart journal. Digital health · 2026Article
- Artificial Intelligence in Cardiovascular Imaging: From Automated Acquisition to Precision Diagnostics and Clinical Decision Support.Medical sciences (Basel, Switzerland) · 2026Review
- Evaluating natural history and treatment response in cardiac amyloidosis: the evolving role of multimodality imaging.European heart journal. Cardiovascular Imaging · 2026Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this review is to provide an update on contemporary and evolving artificial intelligence (AI) methods and their role in diagnosing and managing cardiac amyloidosis (CA). AI is the broadest term which describes a variety of different techniques that enable computers to mimic human intelligence. It is widely used across different diagnostic tests including electrocardiograms, echocardiography, scintigraphy and cardiac magnetic resonance (CMR). Through a comprehensive search among four databases, we identified several insights into clinical applications, diagnostic modalities and different utilization of AI in CA. The elusive nature of CA, which often makes early diagnosis challenging, can greatly benefit from the integration of AI into the diagnostic process. The variability in diagnostic strategies of CA underscores the need for more AI-focused prospective clinical trials to establish evidence-based guidelines for AI-driven diagnostic pathways. Our review highlights the capabilities of AI, particularly in the diagnosis of cardiac amyloidosis.
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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.