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Found 8 papers, 1 papers with code
A Generalizable Deep Learning System for Cardiac MRI
Cardiac MRI allows for a comprehensive assessment of myocardial structure, function, and tissue characteristics.
Echocardiogram Foundation Model -- Application 1: Estimating Ejection Fraction
Cardiovascular diseases stand as the primary global cause of mortality.
Almanac: Retrieval-Augmented Language Models for Clinical Medicine
Large-language models have recently demonstrated impressive zero-shot capabilities in a variety of natural language tasks such as summarization, dialogue generation, and question-answering.
Controlled Comparison of Simulated Hemodynamics across Tricuspid and Bicuspid Aortic Valves
The aortic geometry is based on a healthy patient with no known aortic or valvular disease, which allows us to isolate the hemodynamic consequences of changes to the valve alone.
Simulating time to event prediction with spatiotemporal echocardiography deep learning
Integrating methods for time-to-event prediction with diagnostic imaging modalities is of considerable interest, as accurate estimates of survival requires accounting for censoring of individuals within the observation period.
Medical Imaging and Machine Learning
Advances in computing power, deep learning architectures, and expert labelled datasets have spurred the development of medical imaging artificial intelligence systems that rival clinical experts in a variety of scenarios.
Predicting post-operative right ventricular failure using video-based deep learning
Non-invasive and cost effective in nature, the echocardiogram allows for a comprehensive assessment of the cardiac musculature and valves.
A Design-Based Model of the Aortic Valve for Fluid-Structure Interaction
The solution to these differential equations is referred to as the predicted loaded configuration; it includes the loaded leaflet geometry, fiber orientations and tensions needed to support the prescribed load.
