AIMC Topic: Time Factors

Clear Filters Showing 81 to 90 of 2001 articles

Impact of dairy intake on circulating fatty acids and associations with blood pressure: A randomized crossover trial.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: This study aimed to investigate the effects of high and adequate dairy intake (>4, 2-3 serving/day, respectively) on circulating fatty acids (FAs) and their associations with blood pressure (BP).

An artificial intelligence interpretable tool to predict risk of deep vein thrombosis after endovenous thermal ablation.

Journal of vascular surgery. Venous and lymphatic disorders
OBJECTIVE: Endovenous thermal ablation (EVTA) stands as one of the primary treatments for superficial venous insufficiency. Concern exists about the potential for thromboembolic complications following this procedure. Although rare, those complicatio...

Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.

The international journal of cardiovascular imaging
Real time 2D phase contrast (RTPC) MRI is useful for flow quantification in atrial fibrillation (AF) patients, but data analysis requires time-consuming anatomical contouring for many cardiac time frames. Our goal was to develop a convolutional neura...

Spectral integrated neural networks with large time steps for 2D and 3D transient elastodynamic analysis.

Neural networks : the official journal of the International Neural Network Society
This paper provides a neural network architecture, called spectral integrated neural networks (SINNs), designed to tackle two- and three-dimensional elastodynamic problems. In the SINNs, the second-order time derivatives of displacements are approxim...

SSSLN:Multivariate Time Series Forecasting via Collaborative Dynamic Graph Learning.

Neural networks : the official journal of the International Neural Network Society
Multivariate time series (MTS) forecasting has achieved notable progress through graph modeling. However, existing approaches often face two key challenges. First, traditional dynamic graph learning (DGL) methods typically maintain dynamic graphs dir...

Fast and automatic coronary artery segmentation using nnU-Net for non-contrast enhanced magnetic resonance coronary angiography.

The international journal of cardiovascular imaging
Non-contrast enhanced magnetic resonance coronary angiography (MRCA) is a promising coronary heart disease screening modality. However, its clinical application is hindered by inherent limitations, including low spatial resolution and insufficient co...

Artificial Delayed-phase Technetium-99m MIBI Scintigraphy From Early-phase Scintigraphy Improves Identification of Hyperfunctioning Parathyroid Lesions in Patients With Hyperparathyroidism.

Clinical nuclear medicine
PURPOSE: The aim of this study was to generate and validate artificial delayed-phase technetium-99m methoxyisobutylisonitrile scintigraphy (aMIBI) images from early-phase technetium-99m methoxyisobutylisonitrile scintigraphy (eMIBI) images.

An investigation into the impact of temporality on COVID-19 infection and mortality predictions: new perspective based on Shapley Values.

BMC medical research methodology
INTRODUCTION: Machine learning models have been employed to predict COVID-19 infections and mortality, but many models were built on training and testing sets from different periods. The purpose of this study is to investigate the impact of temporali...

Timing of kidney replacement therapy in critically ill patients: A call to shift the paradigm in the era of artificial intelligence.

Science progress
Acute kidney injury (AKI) is a common condition in intensive care units (ICUs) and is associated with high mortality rates, particularly when kidney replacement therapy (KRT) becomes necessary. The optimal timing for initiating KRT remains a subject ...

Integrated codec decomposed Transformer for long-term series forecasting.

Neural networks : the official journal of the International Neural Network Society
Recently, Transformer-based and multilayer perceptron (MLP) based architectures have formed a competitive landscape in the field of time series forecasting. There is evidence that series decomposition can further enhance the model's ability to percei...