Cardiovascular

Quantitative CT Imaging in Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous condition characterized by di...

Knowledge, attitudes, and practices of cardiovascular health care personnel regarding coronary CTA and AI-assisted diagnosis: a cross-sectional study.

BACKGROUND: Artificial intelligence (AI) holds significant promise for medical applications, particu...

Novel CAC Dispersion and Density Score to Predict Myocardial Infarction and Cardiovascular Mortality.

BACKGROUND: Coronary artery calcification (CAC) provides robust prediction for major adverse cardiov...

Exploratory development of human-machine interaction strategies for post-stroke upper-limb rehabilitation.

BACKGROUND: Stroke and its related complications, place significant burdens on human society in the ...

Artificial intelligence for electrocardiographic diagnosis of perioperative myocardial ischaemia: a scoping review.

BACKGROUND: Perioperative electrocardiographic monitoring can offer immediate detection of myocardia...

Efficient sleep apnea detection using single-lead ECG: A CNN-Transformer-LSTM approach.

BACKGROUND: Sleep apnea (SA), a prevalent sleep-related breathing disorder, disrupts normal respirat...

Deep learning framework for cardiorespiratory disease detection using smartphone IMU sensors.

Respiratory and cardiovascular diseases represent a significant global health burden, underscoring t...

Artificial Intelligence-Enabled ECGs for Atrial Fibrillation Identification and Enhanced Oral Anticoagulant Adoption: A Pragmatic Randomized Clinical Trial.

BACKGROUND: Atrial fibrillation (AF) is often underdiagnosed and undertreated by noncardiologists. T...

The emerging role of artificial intelligence in heart failure.

Heart Failure is a prevalent disease with significant impacts on morbidity and mortality. Heart fail...

Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015-2018.

Cardiometabolic Multimorbidity (CMM) has emerged as one of the primary threats to human health globa...

Predicting carotid atherosclerosis in latent autoimmune diabetes in adult patients using machine learning models: a retrospective study.

BACKGROUND: Latent autoimmune diabetes in adults (LADA) is a slowly progressing form of diabetes wit...

Beyond Recanalization: Machine Learning-Based Insights into Post-Thrombectomy Vascular Morphology in Stroke Patients.

Many stroke patients have poor outcomes despite successful endovascular therapy (EVT). We hypothesiz...

AngioReport: dataset and baseline methods for fundus angiography report generation.

PURPOSE: To develop an annotated fundus angiographic dataset, including fundus fluorescein angiograp...

Digital twin for sex-specific identification of class III antiarrhythmic drugs based on in vitro measurements, computer models, and machine learning tools.

Atrial fibrillation (AF) significantly affects morbidity and mortality rates. Class III antiarrhythm...

From lipids and inflammation to artificial intelligence-driven therapeutics: the 93rd European atherosclerosis society (EAS) congress 2025 in focus.

Toward developing a compact total artificial heart using a soft robotic fluidic transmission system.

Cardiovascular diseases are a leading cause of mortality, with limited possibilities for transplanta...

Predicting and Diagnosing Pneumonia in Patients Undergoing Elective Cardiac Surgery via Machine Learning Analysis of Exhaled Volatile Carbonyl Compounds.

OBJECTIVE: Pneumonia remains one of the most common post-operative complications after elective card...

Contribution of a new super-resolution deep-learning image reconstruction algorithm coupled with an extended matrix to cardiac CT image quality.

Assessing the effect of perfluoroalkyl and polyfluoroalkyl substances on cardiovascular-kidney-metabolic syndrome: Insights from an interpretable machine learning model.

Cardiovascular-kidney-metabolic syndrome (CKM) and its association with exposure to emerging polluta...

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...

A novel XAI framework for explainable AI-ECG using generative counterfactual XAI (GCX).

Generative Counterfactual Explainable Artificial Intelligence (XAI) offers a novel approach to under...