Cardiovascular

Automated echocardiographic left ventricular dimension assessment in dogs using artificial intelligence: Development and validation.

BACKGROUND: Artificial intelligence (AI) could improve accuracy and reproducibility of echocardiogra...

Electrocardiography deep learning models to predict high-risk imaging features in patients with hypertrophic cardiomyopathy: Can it change clinical practice?

Machine learning decision support model for discharge planning in stroke patients.

BACKGROUND/AIM: Efficient discharge for stroke patients is crucial but challenging. The study aimed ...

Low-tube-voltage whole-body CT angiography with extremely low iodine dose: a comparison between hybrid-iterative reconstruction and deep-learning image-reconstruction algorithms.

AIM: To evaluate arterial enhancement, its depiction, and image quality in low-tube potential whole-...

[Artificial intelligence-enhanced electrocardiography : Will it revolutionize diagnosis and management of our patients?].

The use of artificial intelligence (AI) in healthcare has made significant progress in the last 10 y...

Overview and Clinical Applications of Artificial Intelligence and Machine Learning in Cardiac Anesthesiology.

Artificial intelligence- (AI) and machine learning (ML)-based applications are becoming increasingly...

Convolutional neuronal network for identifying single-cell-platelet-platelet-aggregates in human whole blood using imaging flow cytometry.

Imaging flow cytometry is an attractive method to investigate individual cells by optical properties...

Training of a deep learning based digital subtraction angiography method using synthetic data.

BACKGROUND: Digital subtraction angiography (DSA) is a fluoroscopy method primarily used for the dia...

A Q-transform-based deep learning model for the classification of atrial fibrillation types.

According to the World Health Organization (WHO), Atrial Fibrillation (AF) is emerging as a global e...

Assessment of deep learning segmentation for real-time free-breathing cardiac magnetic resonance imaging at rest and under exercise stress.

In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been de...

A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing cardiomegaly in chest X-ray.

Accurate identification and localization of multiple abnormalities are crucial steps in the interpre...

Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

Timely and accurate referral of end-stage heart failure patients for advanced therapies, including h...

Dexterous helical magnetic robot for improved endovascular access.

Treating vascular diseases in the brain requires access to the affected region inside the body. This...

Estimating the risk of sudden death in hypertrophic cardiomyopathy might be solved by artificial intelligence.

Automated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning.

BACKGROUND: A deep learning (DL) model that automatically detects cardiac pathologies on cardiac MRI...

Optimizing High-Resolution MR Angiography: The Synergistic Effects of 3D Wheel Sampling and Deep Learning-Based Reconstruction.

OBJECTIVE: The aim of this study was to assess the utility of the combined use of 3D wheel sampling ...

Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis.

Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myo...

Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning.

Thoracic echocardiography (TTE) can provide sufficient cardiac structure information, evaluate hemod...

Assessing the clinical reasoning of ChatGPT for mechanical thrombectomy in patients with stroke.

BACKGROUND: Artificial intelligence (AI) has become a promising tool in medicine. ChatGPT, a large l...

Automated catheter segmentation and tip detection in cerebral angiography with topology-aware geometric deep learning.

BACKGROUND: Visual perception of catheters and guidewires on x-ray fluoroscopy is essential for neur...

Acute Kidney Injury in Acute Myocardial Infarction and Its Outcome at 3 and 6 Months.

Epidemiological data on the prevalence of acute kidney injury (AKI) in acute coronary syndrome are s...