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Rima Arnaout, MD
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Publications
Rima Arnaout, MD's Publications
Are AI Foundation Models Efficient for Segmentation of Echocardiograms?
Epistasis regulates genetic control of cardiac hypertrophy.
From Bytes to Beats: Overcoming Conceptual and Implementation Challenges for AI in Cardiovascular Care.
Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reports.
PRIME 2.0: An Update to The Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation Checklist.
Self-supervised learning for label-free segmentation in cardiac ultrasound.
The MI-CLAIM-GEN checklist for generative artificial intelligence in health.
X-Factor: Quality Is a Dataset-Intrinsic Property.
Adapting vision-language AI models to cardiology tasks.
Beyond Size and Class Balance: Alpha as a New Dataset Quality Metric for Deep Learning.
Epistasis regulates genetic control of cardiac hypertrophy.
Improving Prenatal Detection of Congenital Heart Disease With a Scalable Composite Analysis of 6 Fetal Cardiac Ultrasound Biometrics.
Learning epistatic polygenic phenotypes with Boolean interactions.
Myocardial Texture Analysis of Echocardiograms in Cardiac Transthyretin Amyloidosis.
Novel Techniques in Imaging Congenital Heart Disease: JACC Scientific Statement.
ChatGPT Helped Me Write This Talk Title, but Can It Read an Echocardiogram?
Deep learning model for prenatal congenital heart disease (CHD) screening generalizes to the community setting and outperforms clinical detection.
Domain-guided data augmentation for deep learning on medical imaging.
ENRICHing medical imaging training sets enables more efficient machine learning.
Epistasis regulates genetic control of cardiac hypertrophy.
greylock: A Python Package for Measuring The Composition of Complex Datasets.
Principles for Health Information Collection, Sharing, and Use: A Policy Statement From the American Heart Association.
Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient Care.
The (Heart and) Soul of a Human Creation: Designing Echocardiography for the Big Data Age.
Gender-based time discrepancy in diagnosis of coronary artery disease based on data analytics of electronic medical records.
Visualizing omicron: COVID-19 deaths vs. cases over time.
An ensemble of neural networks provides expert-level prenatal detection of complex congenital heart disease.
Can Machine Learning Help Simplify the Measurement of Diastolic Function in Echocardiography?
Development and Validation of a Deep Learning Strategy for Automated View Classification of Pediatric Focused Assessment With Sonography for Trauma.
Intelligence-based medicine. Chang AC, editor
Machine Learning and the Future of Cardiovascular Care: JACC State-of-the-Art Review.
Mitral Valve Atlas for Artificial Intelligence Predictions of MitraClip Intervention Outcomes.
Best practices for authors of healthcare-related artificial intelligence manuscripts.
Development and Validation of a Deep Learning Model for Automated View Classification of Pediatric Focused Assessment with Sonography for Trauma (FAST)
Expert-level prenatal detection of complex congenital heart disease from screening ultrasound using deep learning
Learning epistatic polygenic phenotypes with Boolean interactions
Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist.
Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation (PRIME): A Checklist: Reviewed by the American College of Cardiology Healthcare Innovation Council.
Pregnancy complications and premature cardiovascular events among 1.6 million California pregnancies.
Toward a clearer picture of health.
Distinct myocardial lineages break atrial symmetry during cardiogenesis in zebrafish.
Fast and accurate view classification of echocardiograms using deep learning.
Fast and accurate classification of echocardiograms using deep learning
LITTLE FISH, BIG DATA: ZEBRAFISH AS A MODEL FOR CARDIOVASCULAR AND METABOLIC DISEASE.
Neuregulin-1 is essential for nerve plexus formation during cardiac maturation
Neuregulin-1 is essential for nerve plexus formation during cardiac maturation.
A mutation in the atrial-specific myosin light chain gene (MYL4) causes familial atrial fibrillation.
Actin binding GFP allows 4D in vivo imaging of myofilament dynamics in the zebrafish heart and the identification of Erbb2 signaling as a remodeling factor of myofibril architecture.
Recovery of adult zebrafish hearts for high-throughput applications.
Developmental biology: physics adds a twist to gut looping.
Late Recognition of Malignant Vasovagal Syncope.
Genetic and physiologic dissection of the vertebrate cardiac conduction system.
Zebrafish model for human long QT syndrome.
