Cardiovascular

Peripheral Artery Disease

Latest AI and machine learning research in peripheral artery disease for healthcare professionals.

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Showing 148-168 of 7,574 articles
Machine Learning Detects Symptomatic Plaques in Patients With Carotid Atherosclerosis on CT Angiography.

BACKGROUND: This study aimed to develop and validate a computed tomography angiography based machine...

Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?

PURPOSE OF REVIEW: This review evaluates how Artificial Intelligence (AI) enhances atherosclerotic c...

A new machine learning model to predict the prognosis of cardiogenic brain infarction.

Cardiogenic cerebral infarction (CCI) is a disease in which the blood supply to the blood vessels in...

Identifying Cardiovascular Disease Risk Endotypes of Adolescent Major Depressive Disorder Using Exploratory Unsupervised Machine Learning.

OBJECTIVE: Adolescents with major depressive disorder (MDD) are at increased risk of premature ather...

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...

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...

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 ...

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...

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...

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