Peripheral Artery Disease

The effect of head motion on brain age prediction using deep convolutional neural networks.

Deep learning can be used effectively to predict participants' age from brain magnetic resonance ima...

Systematic screening by a heart team and a machine learning approach contribute to unraveling novel risk factors in revascularization candidates with complex coronary artery disease.

INTRODUCTION: The baseline characteristics affecting mortality following percutaneous or surgical re...

Risk prediction model of metabolic syndrome in perimenopausal women based on machine learning.

INTRODUCTION: Metabolic syndrome (MetS) is considered to be an important parameter of cardio-metabol...

Development and multinational validation of an algorithmic strategy for high Lp(a) screening.

Elevated lipoprotein (a) (Lp(a)) is associated with premature atherosclerotic cardiovascular disease...

Radiomics and artificial intelligence: General notions and applications in the carotid vulnerable plaque.

Carotid atherosclerosis plays a substantial role in cardiovascular morbidity and mortality. Given th...

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived techn...

Any region can be perceived equally and effectively on rotation pretext task using full rotation and weighted-region mixture.

In recent years, self-supervised learning has emerged as a powerful approach to learning visual repr...

Prediction and causal inference of hyperuricemia using gut microbiota.

Hyperuricemia (HUA) is a symptom of high blood uric acid (UA) levels, which causes disorders such as...

Design of an actuator with bionic claw hook-suction cup hybrid structure for soft robot.

To improve the adaptability of soft robots to the environment and achieve reliable attachment on var...

Preclinical identification of acute coronary syndrome without high sensitivity troponin assays using machine learning algorithms.

Preclinical management of patients with acute chest pain and their identification as candidates for ...

AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CAC) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis.

INTRODUCTION: Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC...

Integrating machine learning algorithms and single-cell analysis to identify gut microbiota-related macrophage biomarkers in atherosclerotic plaques.

OBJECTIVE: The relationship between macrophages and the gut microbiota in patients with atherosclero...

Predicting Outcomes Following Lower Extremity Endovascular Revascularization Using Machine Learning.

BACKGROUND: Lower extremity endovascular revascularization for peripheral artery disease carries non...

Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories.

This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QC...

On the relationship between various anticoagulants and robot-assisted radical prostatectomy: a single-surgeon serial analysis.

Prostate cancer patients often have other health conditions and take anticoagulants. It was believed...

Development and validation of machine learning models to predict postoperative infarction in moyamoya disease.

OBJECTIVE: Cerebral infarction is a common complication in patients undergoing revascularization sur...

Leveraging Artificial Intelligence to Optimize the Care of Peripheral Artery Disease Patients.

Peripheral artery disease is a major atherosclerotic disease that is associated with poor outcomes s...

Convolutional Neural Networks to Study Contrast-Enhanced Magnetic Resonance Imaging-Based Skeletal Calf Muscle Perfusion in Peripheral Artery Disease.

Peripheral artery disease (PAD) is associated with impaired blood flow in the lower extremities and ...

Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort.

Deep Learning to Estimate Cardiovascular Risk From Chest Radiographs : A Risk Prediction Study.

BACKGROUND: Guidelines for primary prevention of atherosclerotic cardiovascular disease (ASCVD) reco...

Effects of thienopyridine class antiplatelets on bleeding outcomes following robot-assisted radical prostatectomy.

This study aimed to assess the effects of thienopyridine-class antiplatelet agents (including ticlop...