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Rima Arnaout

Showing results (41-50 of 55) with videos related to

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Scientific Reports|February 14, 2025
Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reportsSuganya Subramaniam, Sara Rizvi, Ramya Ramesh, et al.
Plos One|April 16, 2024
Learning epistatic polygenic phenotypes with Boolean interactionsMerle Behr, Karl Kumbier, Aldo Cordova-Palomera, et al.
Nature Medicine|September 10, 2020
Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklistBeau Norgeot, Giorgio Quer, Brett K Beaulieu-Jones, et al.
Plos Biology|May 16, 2008
Genetic and physiologic dissection of the vertebrate cardiac conduction systemNeil C Chi, Robin M Shaw, Benno Jungblut, et al.
Circulation|August 30, 2023
Principles for Health Information Collection, Sharing, and Use: A Policy Statement From the American Heart AssociationKayte Spector-Bagdady, Antonis A Armoundas, Rima Arnaout, et al.
JACC. Cardiovascular Imaging|July 22, 2023
Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient CareDamini Dey, Rima Arnaout, Sameer Antani, et al.
Nature Communications|April 13, 2016
A mutation in the atrial-specific myosin light chain gene (MYL4) causes familial atrial fibrillationNathan Orr, Rima Arnaout, Lorne J Gula, et al.
Journal of the American Society of Echocardiography : Official Publication of the American Society of Echocardiography|May 16, 2023
The (Heart and) Soul of a Human Creation: Designing Echocardiography for the Big Data AgeRima Arnaout, Rebecca T Hahn, Judy W Hung, et al.
Nature Medicine|February 6, 2025
The MI-CLAIM-GEN checklist for generative artificial intelligence in healthBrenda Y Miao, Irene Y Chen, Christopher Y K Williams, et al.
JACC. Cardiovascular Imaging|September 2, 2025
PRIME 2.0: An Update to The Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation ChecklistNobuyuki Kagiyama, Márton Tokodi, Quincy A Hathaway, et al.
Pageof 6

Showing results (41-50 of 55) with videos related to

Sort By:
Pageof 6
Scientific Reports|February 14, 2025
Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reportsSuganya Subramaniam, Sara Rizvi, Ramya Ramesh, et al.
Plos One|April 16, 2024
Learning epistatic polygenic phenotypes with Boolean interactionsMerle Behr, Karl Kumbier, Aldo Cordova-Palomera, et al.
Nature Medicine|September 10, 2020
Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklistBeau Norgeot, Giorgio Quer, Brett K Beaulieu-Jones, et al.
Plos Biology|May 16, 2008
Genetic and physiologic dissection of the vertebrate cardiac conduction systemNeil C Chi, Robin M Shaw, Benno Jungblut, et al.
Circulation|August 30, 2023
Principles for Health Information Collection, Sharing, and Use: A Policy Statement From the American Heart AssociationKayte Spector-Bagdady, Antonis A Armoundas, Rima Arnaout, et al.
JACC. Cardiovascular Imaging|July 22, 2023
Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient CareDamini Dey, Rima Arnaout, Sameer Antani, et al.
Nature Communications|April 13, 2016
A mutation in the atrial-specific myosin light chain gene (MYL4) causes familial atrial fibrillationNathan Orr, Rima Arnaout, Lorne J Gula, et al.
Journal of the American Society of Echocardiography : Official Publication of the American Society of Echocardiography|May 16, 2023
The (Heart and) Soul of a Human Creation: Designing Echocardiography for the Big Data AgeRima Arnaout, Rebecca T Hahn, Judy W Hung, et al.
Nature Medicine|February 6, 2025
The MI-CLAIM-GEN checklist for generative artificial intelligence in healthBrenda Y Miao, Irene Y Chen, Christopher Y K Williams, et al.
JACC. Cardiovascular Imaging|September 2, 2025
PRIME 2.0: An Update to The Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation ChecklistNobuyuki Kagiyama, Márton Tokodi, Quincy A Hathaway, et al.
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