AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Heart

Showing 131 to 140 of 453 articles

Clear Filters

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review.

Computers in biology and medicine
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality globally. At early stages, CVDs appear with minor symptoms and progressively get worse. The majority of people experience symptoms such as exhaustion, ...

A discontinuity-preserving regularization for deep learning-based cardiac image registration.

Physics in medicine and biology
. Sliding motion may occur between organs in anatomical regions due to respiratory motion and heart beating. This issue is often neglected in previous studies, resulting in poor image registration performance. A new approach is proposed to handle dis...

Left ventricle segmentation combining deep learning and deformable models with anatomical constraints.

Journal of biomedical informatics
Segmentation of the left ventricle is a key approach in Cardiac Magnetic Resonance Imaging for calculating biomarkers in diagnosis. Since there is substantial effort required from the expert, many automatic segmentation methods have been proposed, in...

Self-supervised structural similarity-based convolutional neural network for cardiac diffusion tensor image denoising.

Medical physics
BACKGROUND: Diffusion tensor imaging (DTI) is a promising technique for non-invasively investigating the myocardial fiber structures of human heart. However, low signal-to-noise ratio (SNR) has been a major limit of cardiac DTI to prevent us from det...

Cardiac arrest prediction in smokers using enhanced Artificial Bee Colony algorithm with stacked autoencoder model.

Computer methods in biomechanics and biomedical engineering
In the recent times, the cardiac arrest is a severe heart disease, which results in millions of annual casualties. In this article, the heart rate variability (HRV) parameters are used for predicting cardiac arrest in smokers based on the deep learni...

Deep Learning on Bone Scintigraphy to Detect Abnormal Cardiac Uptake at Risk of Cardiac Amyloidosis.

JACC. Cardiovascular imaging
BACKGROUND: Cardiac uptake on technetium-99m whole-body scintigraphy (WBS) is almost pathognomonic of transthyretin cardiac amyloidosis. The rare false positives are often related to light-chain cardiac amyloidosis. However, this scintigraphic featur...

Explainable Artificial Intelligence and Cardiac Imaging: Toward More Interpretable Models.

Circulation. Cardiovascular imaging
Artificial intelligence applications have shown success in different medical and health care domains, and cardiac imaging is no exception. However, some machine learning models, especially deep learning, are considered black box as they do not provid...

Deep learning-enabled analysis of medical images identifies cardiac sphericity as an early marker of cardiomyopathy and related outcomes.

Med (New York, N.Y.)
BACKGROUND: Quantification of chamber size and systolic function is a fundamental component of cardiac imaging. However, the human heart is a complex structure with significant uncharacterized phenotypic variation beyond traditional metrics of size a...

Epoch and accuracy based empirical study for cardiac MRI segmentation using deep learning technique.

PeerJ
Cardiac magnetic resonance imaging (CMRI) is a non-invasive imaging technique to analyse the structure and function of the heart. It was enhanced considerably over several years to deliver functional information for diagnosing and managing cardiovasc...