The advancements in genomics and biomedical technologies have generated vast amounts
of biological and physiological data, which present opportunities for understanding human …

Objectives To develop a computed tomography (CT) radiomics-based interpretable machine
learning (ML) model to predict the pathological grade of pancreatic neuroendocrine tumors …

Cardiac MRI is used to diagnose and treat patients with a multitude of cardiovascular
diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and …

Introduction Intravenous immunoglobulin (IVIG) resistance is an independent risk factor for
the development of coronary artery lesions (CAL) in patients with Kawasaki disease (KD) …

The recent prevalence of publicly accessible, large medical imaging datasets has led to a
proliferation of artificial intelligence (AI) models for cardiovascular image classification and …

deep learning solution to detect left ventricular structural abnormalities with chest X-rays:
towards trustworthy AI in cardiology | European Heart Journal | Oxford Academic Skip to Main …

Cardiovascular diseases remain a significant health burden, with imaging modalities like
echocardiography, cardiac computed tomography, and cardiac magnetic resonance …

Background Artificial intelligence (AI) that utilizes deep learning (DL) has potential for
systemic disease prediction using retinal imaging. The retina's unique features enable non …

Congenital heart disease (CHD) is a severe health risk for newborns. Early detection of
abnormalities in fetal cardiac structure and function during pregnancy can help patients seek …

Objectives Hypoxemia as a common complication in colonoscopy under sedation and may
result in serious consequences. Unfortunately, a hypoxemia prediction model for outpatient …