Cardiovascular

Fetal arrhythmia detection method based on QCNN-BiLSTM.

Refining cardiac segmentation from MRI volumes with CT labels for fine anatomy of the ascending aorta.

Magnetic resonance imaging (MRI) is time-consuming, posing challenges in capturing clear images of m...

Big data and cardiovascular risk-insights into obesity, diabetes, and coronary heart disease.

BACKGROUND: Cardiovascular diseases (CVD) remain a major global health burden. Obesity and type 2 di...

Artificial Intelligence for Detection of Prognostically Significant Left Ventricular Dysfunction From Echocardiography.

BACKGROUND: Identification of left ventricular (LV) dysfunction following echocardiographic investig...

Inflammation-related 5-hydroxymethylation signatures as markers for clinical presentations of coronary artery disease.

BACKGROUND: Coronary angiography remains the gold standard for diagnosing coronary artery disease (C...

Prospective Registry Study on Thermal Liver Ablation of Primary and Secondary Liver Tumours Named the A-IMAGIO Study.

PURPOSE: The long-term objective of the Ablation-IMaging and Advanced Guidance for workflow optimiza...

Complete AI-Enabled Echocardiography Interpretation With Multitask Deep Learning.

IMPORTANCE: Echocardiography is a cornerstone of cardiovascular care, but relies on expert interpret...

Electrocardiogram-Based Artificial Intelligence for Detection of Low Ejection Fraction: A Contemporary Review.

Artificial intelligence (AI) is transforming the role of electrocardiography (ECG) in cardiovascular...

Lipidomic profiling of human adiposomes identifies specific lipid shifts linked to obesity and cardiometabolic risk.

BACKGROUNDObesity, a growing health concern, often leads to metabolic disturbances, systemic inflamm...

Machine learning-based hybrid risk estimation system (ERES) in cardiac surgery: Supplementary insights from the ASA score analysis.

Accurate prediction of postoperative mortality risk after cardiac surgery is essential to improve pa...

From "time is brain" to "time is collaterals": updates on the role of cerebral collateral circulation in stroke.

BACKGROUND: Acute ischemic stroke (AIS) remains the leading cause of mortality and disability worldw...

Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits.

Electronic health records, biobanks, and wearable biosensors enable the collection of multiple healt...

Correction: Machine learning for cardio-oncology: predicting global longitudinal strain from conventional echocardiographic measurements in cancer patients.

Exploring the potential biomarkers between stroke and obstructive sleep apnea by WGCNA and machine learning.

BACKGROUND: Ischemic stroke (IS) and obstructive sleep apnea (OSA) are highly prevalent disorders wi...

Emergency radiology: roadmap for radiology departments.

Emergency radiology has evolved into a significant subspecialty over the past 2 decades, facing uniq...

The Impact of Artificial Intelligence on Women's Cardiovascular Disease Care.

PURPOSE OF REVIEW: To review current artificial intelligence (AI) applications impacting cardiovascu...

Prevalence and determinants of hypertension among adults of reproductive age in Tanzania: analysis of a cross-sectional Demographic and Health Survey.

OBJECTIVE: We aimed to estimate prevalence and identify determinants of hypertension in adults aged ...

Data extraction from free-text stroke CT reports using GPT-4o and Llama-3.3-70B: the impact of annotation guidelines.

BACKGROUND: To evaluate the impact of an annotation guideline on the performance of large language m...

Non-Invasive Diagnosis of Chronic Myocardial Infarction via Composite In-Silico-Human Data Learning.

Myocardial infarction (MI) continues to be a leading cause of death worldwide. The precise quantific...

Association of DNA methylation epigenetic markers with all-cause mortality and cardiovascular disease-related mortality in diabetic population: a machine learning-based retrospective cohort study.

BACKGROUND: Diabetes has a large and diverse population, with individuals exhibiting significant het...

Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study.

BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walk...