Cardiovascular

Acute Coronary Syndrome

Latest AI and machine learning research in acute coronary syndrome for healthcare professionals.

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Showing 1-21 of 6,674 articles
Engineering the Interfacial Charge Transfer Dynamics by Plasmonic S-Scheme Heterojunctions for Machine-Learning-Assisted Dual-Mode Immunoassays.

The development of photoelectrochemical (PEC)-coupled dual-mode biosensors, combined with multivaria...

AI-enhanced recognition of occlusions in acute coronary syndrome (AERO-ACS): a retrospective study.

BACKGROUND: Artificial intelligence (AI) augmentation of ECG assessment has significant potential to...

Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation.

Atrial fibrillation (AF) increases the risk of adverse cardiovascular events, yet the underlying bio...

AI-Guided Decision Support in Acute Cardiac Care: From Chest Pain to STEMI.

Artificial intelligence (AI) is rapidly transforming the landscape of acute cardiac care, offering n...

Machine Learning-based Classification of Adrenal Tumors Using Clinical, Hormonal, and Body Composition Data.

OBJECTIVE: Accurate diagnosis of adrenal tumors, including mild autonomous cortisol secretion (MACS)...

Deep Learning-Based Acceleration in MRI: Current Landscape and Clinical Applications in Neuroradiology.

Magnetic resonance imaging (MRI) is a cornerstone of neuroimaging, providing unparalleled soft-tissu...

Super Learner Enhances Postoperative Complication Prediction in Colorectal Surgery.

OBJECTIVE: To determine if a Super Learner (SL) machine learning approach could improve the predicti...

Analysis of aPTT predictors after unfractionated heparin administration in intensive care units using machine learning models.

OBJECTIVES: Predicting optimal coagulation control using heparin in intensive care units (ICUs) rema...

Deep learning reconstruction enhances image quality in contrast-enhanced CT venography for deep vein thrombosis.

PURPOSE: This study aimed to evaluate and compare the diagnostic performance and image quality of de...

Monitoring systemic ventriculoarterial coupling after cardiac surgery using continuous transoesophageal echocardiography and deep learning.

Deterioration of ventriculoarterial coupling is detrimental to cardiovascular and left ventricular f...

Construction of a Machine Learning-Based Clopidogrel Resistance Risk Prediction Model.

Clopidogrel is extensively utilized for the prevention and treatment of cardiovascular, cerebrovascu...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracereb...

Molecular property prediction in the ultra-low data regime.

Data scarcity remains a major obstacle to effective machine learning in molecular property predictio...

Enhanced machine learning models for predicting three-year mortality in Non-STEMI patients aged 75 and above.

BACKGROUND: Non-ST segment elevation myocardial infarction (Non-STEMI) is a severe cardiovascular co...

Method for Predict Stenosis of Arteriovenous Fistula Patients Based on Machine Learning.

OBJECTIVES: Arteriovenous fistula (AVF) is the most ideal vascular access for hemodialysis. People w...

Machine learning-based prediction model for arteriovenous fistula thrombosis risk: a retrospective cohort study from 2017 to 2024.

BACKGROUND: Thrombosis of arteriovenous fistulas represents a prevalent complication among patients ...

A modified generative adversarial networks method for assisting the diagnosis of deep venous thrombosis complications in stroke patients.

Discriminate deep vein thrombosis, one of the complications in early stroke patients, in order to as...

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