AIMC Topic: Time Factors

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Consensus synchronization via quantized iterative learning for coupled fractional-order time-delayed competitive neural networks with input sharing.

Neural networks : the official journal of the International Neural Network Society
This paper presents the D-type distributed iterative learning control protocol to synchronize fractional-order competitive neural networks with time delay within a finite time frame. Firstly, the input sharing strategy of such desired competitive neu...

Association between atherogenicity indices and prediabetes: a 5-year retrospective cohort study in a general Chinese physical examination population.

Cardiovascular diabetology
BACKGROUND AND OBJECTIVE: Atherogenicity indices have emerged as promising markers for cardiometabolic disorders, yet their relationship with prediabetes risk remains unclear. This study aimed to comprehensively evaluate the associations between six ...

Dual-stream interactive networks with pearson-mask awareness for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society
Multivariate time series forecasting (MTSF) aims to predict time series data containing multiple variates, which requires the consideration of both intra-series temporal trends and inter-series interactions. Benefiting from the success of Transformer...

Entity replacement strategy for temporal knowledge graph query relaxation.

Neural networks : the official journal of the International Neural Network Society
The temporal knowledge graph (TKG) query enables the retrieval of candidate answer lists by addressing questions that involve temporal constraints, regarded as a crucial downstream task in the realm of the temporal knowledge graph. Existing methods p...

Characterization of Effective Half-Life for Instant Single-Time-Point Dosimetry Using Machine Learning.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Single-time-point (STP) image-based dosimetry offers a more convenient approach for clinical practice in radiopharmaceutical therapy (RPT) compared with conventional multiple-time-point image-based dosimetry. Despite numerous advancements, current ST...

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...

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 ...