ArticleJournal of personalized medicine2021
Convolutional Neural Networks for Fully Automated Diagnosis of Cardiac Amyloidosis by Cardiac Magnetic Resonance Imaging.
Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 30 citations in OpenAlex.
- Natural Language Processing Framework in Early Detection of Amyloidosis: The ALARM Study.JACC. Advances · 2026Article
- Deep Learning and Cardiovascular Diseases: An Updated Narrative Review.Journal of clinical medicine · 2026Review
- Myocardial radiomics of non-ischemic cardiomyopathy using cardiovascular magnetic resonance: current perspectives and future directions.Frontiers in cardiovascular medicine · 2026Review
- Identifying implementation strategies to increase the early detection of cardiac amyloidosis: a pre-implementation study.Frontiers in cardiovascular medicine · 2026Article
- Bridging the Gap in AL and ATTR Cardiac Amyloidosis: Integrating Histopathology, Biomarkers, and Multimodal Imaging for Subtype-Specific Diagnosis.Reviews in cardiovascular medicine · 2026Review
- Deep learning for cardiac MRI: performance evidence and barriers to clinical integration. A Systematic Review and Meta-Analysis.European heart journal. Imaging methods and practice · 2026Article
- Assessing the quality of reporting in artificial intelligence/machine learning research for cardiac amyloidosis.JAMIA open · 2025Article
- The Role of Artificial Intelligence in Cardiac Amyloidosis: A Focus on Diagnosis and Clinical Application.Journal of cardiovascular development and disease · 2025Review
- Hearts, Data, and Artificial Intelligence Wizardry: From Imitation to Innovation in Cardiovascular Care.Biomedicines · 2025Review
- Leveraging a Vision Transformer Model to Improve Diagnostic Accuracy of Cardiac Amyloidosis With Cardiac Magnetic Resonance.JACC. Cardiovascular imaging · 2025Article
- Review
- The Role of Artificial Intelligence in the Detection of Cardiac Amyloidosis: A Systematic Review.Cureus · 2025Review
- Multi-modality artificial intelligence-based transthyretin amyloid cardiomyopathy detection in patients with severe aortic stenosis.European journal of nuclear medicine and molecular imaging · 2025Article
- Recent Progress of Cardiac MRI for Nuclear Medicine Professionals.Nuclear medicine and molecular imaging · 2024Review
- Review
- How Artificial Intelligence Can Enhance the Diagnosis of Cardiac Amyloidosis: A Review of Recent Advances and Challenges.Journal of cardiovascular development and disease · 2024Review
- Automated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning.BMC medical imaging · 2024Article
- Examining the Difficulties in Identifying and Handling Cardiac Amyloidosis; Acquiring Important Knowledge and Robust Treatment Methods.Cardiovascular & hematological disorders drug targets · 2024Review
- Deep Learning to Classify AL versus ATTR Cardiac Amyloidosis MR Images.Biomedicines · 2023Article
- Cardiac Disease: Diagnosis, Treatment, and Outcomes.Journal of personalized medicine · 2022Article
Corrections and comments
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Authors and funding
20 authors at 2 institutions in 1 country.
Funding
Abstract
aimsWe tested the hypothesis that artificial intelligence (AI)-powered algorithms applied to cardiac magnetic resonance (CMR) images could be able to detect the potential patterns of cardiac amyloidosis (CA). Readers in CMR centers with a low volume of referrals for the detection of myocardial storage diseases or a low volume of CMRs, in general, may overlook CA. In light of the growing prevalence of the disease and emerging therapeutic options, there is an urgent need to avoid misdiagnoses. METHODS AND
resultsUsing CMR data from 502 patients (CA:
conclusionsApplying AI to CMR to diagnose CA may set a remarkable milestone in an attempt to establish a fully computational diagnostic path for the diagnosis of CA, in order to support the complex diagnostic work-up requiring a profound knowledge of experts from different disciplines.
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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.